Deprecated (16384): The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 73 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php. [CORE/src/Core/functions.php, line 311]Code Context
trigger_error($message, E_USER_DEPRECATED);
}
$message = 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 73 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.' $stackFrame = (int) 1 $trace = [ (int) 0 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ServerRequest.php', 'line' => (int) 2421, 'function' => 'deprecationWarning', 'args' => [ (int) 0 => 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead.' ] ], (int) 1 => [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 73, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) {}, 'type' => '->', 'args' => [ (int) 0 => 'catslug' ] ], (int) 2 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Controller/Controller.php', 'line' => (int) 610, 'function' => 'printArticle', 'class' => 'App\Controller\ArtileDetailController', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 3 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 120, 'function' => 'invokeAction', 'class' => 'Cake\Controller\Controller', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 4 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 94, 'function' => '_invoke', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(App\Controller\ArtileDetailController) {} ] ], (int) 5 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/BaseApplication.php', 'line' => (int) 235, 'function' => 'dispatch', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 6 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Http\BaseApplication', 'object' => object(App\Application) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 7 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/RoutingMiddleware.php', 'line' => (int) 162, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 8 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\RoutingMiddleware', 'object' => object(Cake\Routing\Middleware\RoutingMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 9 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/AssetMiddleware.php', 'line' => (int) 88, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 10 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\AssetMiddleware', 'object' => object(Cake\Routing\Middleware\AssetMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 11 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Middleware/ErrorHandlerMiddleware.php', 'line' => (int) 96, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 12 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Error\Middleware\ErrorHandlerMiddleware', 'object' => object(Cake\Error\Middleware\ErrorHandlerMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 13 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 51, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 14 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Server.php', 'line' => (int) 98, 'function' => 'run', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\MiddlewareQueue) {}, (int) 1 => object(Cake\Http\ServerRequest) {}, (int) 2 => object(Cake\Http\Response) {} ] ], (int) 15 => [ 'file' => '/home/brlfuser/public_html/webroot/index.php', 'line' => (int) 39, 'function' => 'run', 'class' => 'Cake\Http\Server', 'object' => object(Cake\Http\Server) {}, 'type' => '->', 'args' => [] ] ] $frame = [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 73, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) { trustProxy => false [protected] params => [ [maximum depth reached] ] [protected] data => [[maximum depth reached]] [protected] query => [[maximum depth reached]] [protected] cookies => [[maximum depth reached]] [protected] _environment => [ [maximum depth reached] ] [protected] url => 'latest-news-updates/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077/print' [protected] base => '' [protected] webroot => '/' [protected] here => '/latest-news-updates/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077/print' [protected] trustedProxies => [[maximum depth reached]] [protected] _input => null [protected] _detectors => [ [maximum depth reached] ] [protected] _detectorCache => [ [maximum depth reached] ] [protected] stream => object(Zend\Diactoros\PhpInputStream) {} [protected] uri => object(Zend\Diactoros\Uri) {} [protected] session => object(Cake\Http\Session) {} [protected] attributes => [[maximum depth reached]] [protected] emulatedAttributes => [ [maximum depth reached] ] [protected] uploadedFiles => [[maximum depth reached]] [protected] protocol => null [protected] requestTarget => null [private] deprecatedProperties => [ [maximum depth reached] ] }, 'type' => '->', 'args' => [ (int) 0 => 'catslug' ] ]deprecationWarning - CORE/src/Core/functions.php, line 311 Cake\Http\ServerRequest::offsetGet() - CORE/src/Http/ServerRequest.php, line 2421 App\Controller\ArtileDetailController::printArticle() - APP/Controller/ArtileDetailController.php, line 73 Cake\Controller\Controller::invokeAction() - CORE/src/Controller/Controller.php, line 610 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 120 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51 Cake\Http\Server::run() - CORE/src/Http/Server.php, line 98
Deprecated (16384): The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 74 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php. [CORE/src/Core/functions.php, line 311]Code Context
trigger_error($message, E_USER_DEPRECATED);
}
$message = 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 74 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.' $stackFrame = (int) 1 $trace = [ (int) 0 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ServerRequest.php', 'line' => (int) 2421, 'function' => 'deprecationWarning', 'args' => [ (int) 0 => 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead.' ] ], (int) 1 => [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 74, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) {}, 'type' => '->', 'args' => [ (int) 0 => 'artileslug' ] ], (int) 2 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Controller/Controller.php', 'line' => (int) 610, 'function' => 'printArticle', 'class' => 'App\Controller\ArtileDetailController', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 3 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 120, 'function' => 'invokeAction', 'class' => 'Cake\Controller\Controller', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 4 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 94, 'function' => '_invoke', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(App\Controller\ArtileDetailController) {} ] ], (int) 5 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/BaseApplication.php', 'line' => (int) 235, 'function' => 'dispatch', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 6 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Http\BaseApplication', 'object' => object(App\Application) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 7 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/RoutingMiddleware.php', 'line' => (int) 162, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 8 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\RoutingMiddleware', 'object' => object(Cake\Routing\Middleware\RoutingMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 9 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/AssetMiddleware.php', 'line' => (int) 88, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 10 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\AssetMiddleware', 'object' => object(Cake\Routing\Middleware\AssetMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 11 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Middleware/ErrorHandlerMiddleware.php', 'line' => (int) 96, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 12 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Error\Middleware\ErrorHandlerMiddleware', 'object' => object(Cake\Error\Middleware\ErrorHandlerMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 13 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 51, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 14 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Server.php', 'line' => (int) 98, 'function' => 'run', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\MiddlewareQueue) {}, (int) 1 => object(Cake\Http\ServerRequest) {}, (int) 2 => object(Cake\Http\Response) {} ] ], (int) 15 => [ 'file' => '/home/brlfuser/public_html/webroot/index.php', 'line' => (int) 39, 'function' => 'run', 'class' => 'Cake\Http\Server', 'object' => object(Cake\Http\Server) {}, 'type' => '->', 'args' => [] ] ] $frame = [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 74, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) { trustProxy => false [protected] params => [ [maximum depth reached] ] [protected] data => [[maximum depth reached]] [protected] query => [[maximum depth reached]] [protected] cookies => [[maximum depth reached]] [protected] _environment => [ [maximum depth reached] ] [protected] url => 'latest-news-updates/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077/print' [protected] base => '' [protected] webroot => '/' [protected] here => '/latest-news-updates/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077/print' [protected] trustedProxies => [[maximum depth reached]] [protected] _input => null [protected] _detectors => [ [maximum depth reached] ] [protected] _detectorCache => [ [maximum depth reached] ] [protected] stream => object(Zend\Diactoros\PhpInputStream) {} [protected] uri => object(Zend\Diactoros\Uri) {} [protected] session => object(Cake\Http\Session) {} [protected] attributes => [[maximum depth reached]] [protected] emulatedAttributes => [ [maximum depth reached] ] [protected] uploadedFiles => [[maximum depth reached]] [protected] protocol => null [protected] requestTarget => null [private] deprecatedProperties => [ [maximum depth reached] ] }, 'type' => '->', 'args' => [ (int) 0 => 'artileslug' ] ]deprecationWarning - CORE/src/Core/functions.php, line 311 Cake\Http\ServerRequest::offsetGet() - CORE/src/Http/ServerRequest.php, line 2421 App\Controller\ArtileDetailController::printArticle() - APP/Controller/ArtileDetailController.php, line 74 Cake\Controller\Controller::invokeAction() - CORE/src/Controller/Controller.php, line 610 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 120 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51 Cake\Http\Server::run() - CORE/src/Http/Server.php, line 98
Warning (512): Unable to emit headers. Headers sent in file=/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Debugger.php line=853 [CORE/src/Http/ResponseEmitter.php, line 48]Code Contextif (Configure::read('debug')) {
trigger_error($message, E_USER_WARNING);
} else {
$response = object(Cake\Http\Response) { 'status' => (int) 200, 'contentType' => 'text/html', 'headers' => [ 'Content-Type' => [ [maximum depth reached] ] ], 'file' => null, 'fileRange' => [], 'cookies' => object(Cake\Http\Cookie\CookieCollection) {}, 'cacheDirectives' => [], 'body' => '<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <link rel="canonical" href="https://im4change.in/<pre class="cake-error"><a href="javascript:void(0);" onclick="document.getElementById('cakeErr6815bc37e08cf-trace').style.display = (document.getElementById('cakeErr6815bc37e08cf-trace').style.display == 'none' ? '' : 'none');"><b>Notice</b> (8)</a>: Undefined variable: urlPrefix [<b>APP/Template/Layout/printlayout.ctp</b>, line <b>8</b>]<div id="cakeErr6815bc37e08cf-trace" class="cake-stack-trace" style="display: none;"><a href="javascript:void(0);" onclick="document.getElementById('cakeErr6815bc37e08cf-code').style.display = (document.getElementById('cakeErr6815bc37e08cf-code').style.display == 'none' ? '' : 'none')">Code</a> <a href="javascript:void(0);" onclick="document.getElementById('cakeErr6815bc37e08cf-context').style.display = (document.getElementById('cakeErr6815bc37e08cf-context').style.display == 'none' ? '' : 'none')">Context</a><pre id="cakeErr6815bc37e08cf-code" class="cake-code-dump" style="display: none;"><code><span style="color: #000000"><span style="color: #0000BB"></span><span style="color: #007700"><</span><span style="color: #0000BB">head</span><span style="color: #007700">> </span></span></code> <span class="code-highlight"><code><span style="color: #000000"> <link rel="canonical" href="<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">Configure</span><span style="color: #007700">::</span><span style="color: #0000BB">read</span><span style="color: #007700">(</span><span style="color: #DD0000">'SITE_URL'</span><span style="color: #007700">); </span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$urlPrefix</span><span style="color: #007700">;</span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">category</span><span style="color: #007700">-></span><span style="color: #0000BB">slug</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>/<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">seo_url</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>.html"/> </span></code></span> <code><span style="color: #000000"><span style="color: #0000BB"> </span><span style="color: #007700"><</span><span style="color: #0000BB">meta http</span><span style="color: #007700">-</span><span style="color: #0000BB">equiv</span><span style="color: #007700">=</span><span style="color: #DD0000">"Content-Type" </span><span style="color: #0000BB">content</span><span style="color: #007700">=</span><span style="color: #DD0000">"text/html; charset=utf-8"</span><span style="color: #007700">/> </span></span></code></pre><pre id="cakeErr6815bc37e08cf-context" class="cake-context" style="display: none;">$viewFile = '/home/brlfuser/public_html/src/Template/Layout/printlayout.ctp' $dataForView = [ 'article_current' => object(App\Model\Entity\Article) { 'id' => (int) 29023, 'title' => 'Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'subheading' => '', 'description' => '<div align="justify"> -Business Standard<br /> <br /> <em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /> </em><br /> As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /> <br /> In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> &quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 29023, 'metaTitle' => 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'metaKeywords' => 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population', 'metaDesc' => ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...', 'disp' => '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />&quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 29023, 'title' => 'Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'subheading' => '', 'description' => '<div align="justify"> -Business Standard<br /> <br /> <em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /> </em><br /> As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /> <br /> In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> &quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {}, (int) 1 => object(Cake\ORM\Entity) {}, (int) 2 => object(Cake\ORM\Entity) {}, (int) 3 => object(Cake\ORM\Entity) {}, (int) 4 => object(Cake\ORM\Entity) {}, (int) 5 => object(Cake\ORM\Entity) {}, (int) 6 => object(Cake\ORM\Entity) {}, (int) 7 => object(Cake\ORM\Entity) {}, (int) 8 => object(Cake\ORM\Entity) {}, (int) 9 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 29023 $metaTitle = 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee' $metaKeywords = 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population' $metaDesc = ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...' $disp = '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />&quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'</pre><pre class="stack-trace">include - APP/Template/Layout/printlayout.ctp, line 8 Cake\View\View::_evaluate() - CORE/src/View/View.php, line 1413 Cake\View\View::_render() - CORE/src/View/View.php, line 1374 Cake\View\View::renderLayout() - CORE/src/View/View.php, line 927 Cake\View\View::render() - CORE/src/View/View.php, line 885 Cake\Controller\Controller::render() - CORE/src/Controller/Controller.php, line 791 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 126 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51</pre></div></pre>latest-news-updates/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077.html"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <link href="https://im4change.in/css/control.css" rel="stylesheet" type="text/css" media="all"/> <title>LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee | Im4change.org</title> <meta name="description" content=" -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are..."/> <script src="https://im4change.in/js/jquery-1.10.2.js"></script> <script type="text/javascript" src="https://im4change.in/js/jquery-migrate.min.js"></script> <script language="javascript" type="text/javascript"> $(document).ready(function () { var img = $("img")[0]; // Get my img elem var pic_real_width, pic_real_height; $("<img/>") // Make in memory copy of image to avoid css issues .attr("src", $(img).attr("src")) .load(function () { pic_real_width = this.width; // Note: $(this).width() will not pic_real_height = this.height; // work for in memory images. }); }); </script> <style type="text/css"> @media screen { div.divFooter { display: block; } } @media print { .printbutton { display: none !important; } } </style> </head> <body> <table cellpadding="0" cellspacing="0" border="0" width="98%" align="center"> <tr> <td class="top_bg"> <div class="divFooter"> <img src="https://im4change.in/images/logo1.jpg" height="59" border="0" alt="Resource centre on India's rural distress" style="padding-top:14px;"/> </div> </td> </tr> <tr> <td id="topspace"> </td> </tr> <tr id="topspace"> <td> </td> </tr> <tr> <td height="50" style="border-bottom:1px solid #000; padding-top:10px;" class="printbutton"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> <tr> <td width="100%"> <h1 class="news_headlines" style="font-style:normal"> <strong>Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee</strong></h1> </td> </tr> <tr> <td width="100%" style="font-family:Arial, 'Segoe Script', 'Segoe UI', sans-serif, serif"><font size="3"> <div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />"It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div> </font> </td> </tr> <tr> <td> </td> </tr> <tr> <td height="50" style="border-top:1px solid #000; border-bottom:1px solid #000;padding-top:10px;"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> </table></body> </html>' } $maxBufferLength = (int) 8192 $file = '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Debugger.php' $line = (int) 853 $message = 'Unable to emit headers. 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'' : 'none')">Context</a><pre id="cakeErr6815bc37e08cf-code" class="cake-code-dump" style="display: none;"><code><span style="color: #000000"><span style="color: #0000BB"></span><span style="color: #007700"><</span><span style="color: #0000BB">head</span><span style="color: #007700">> </span></span></code> <span class="code-highlight"><code><span style="color: #000000"> <link rel="canonical" href="<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">Configure</span><span style="color: #007700">::</span><span style="color: #0000BB">read</span><span style="color: #007700">(</span><span style="color: #DD0000">'SITE_URL'</span><span style="color: #007700">); </span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$urlPrefix</span><span style="color: #007700">;</span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">category</span><span style="color: #007700">-></span><span style="color: #0000BB">slug</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>/<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">seo_url</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>.html"/> </span></code></span> <code><span style="color: #000000"><span style="color: #0000BB"> </span><span style="color: #007700"><</span><span style="color: #0000BB">meta http</span><span style="color: #007700">-</span><span style="color: #0000BB">equiv</span><span style="color: #007700">=</span><span style="color: #DD0000">"Content-Type" </span><span style="color: #0000BB">content</span><span style="color: #007700">=</span><span style="color: #DD0000">"text/html; charset=utf-8"</span><span style="color: #007700">/> </span></span></code></pre><pre id="cakeErr6815bc37e08cf-context" class="cake-context" style="display: none;">$viewFile = '/home/brlfuser/public_html/src/Template/Layout/printlayout.ctp' $dataForView = [ 'article_current' => object(App\Model\Entity\Article) { 'id' => (int) 29023, 'title' => 'Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'subheading' => '', 'description' => '<div align="justify"> -Business Standard<br /> <br /> <em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /> </em><br /> As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /> <br /> In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> &quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 29023, 'metaTitle' => 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'metaKeywords' => 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population', 'metaDesc' => ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...', 'disp' => '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />&quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 29023, 'title' => 'Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'subheading' => '', 'description' => '<div align="justify"> -Business Standard<br /> <br /> <em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /> </em><br /> As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /> <br /> In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> &quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {}, (int) 1 => object(Cake\ORM\Entity) {}, (int) 2 => object(Cake\ORM\Entity) {}, (int) 3 => object(Cake\ORM\Entity) {}, (int) 4 => object(Cake\ORM\Entity) {}, (int) 5 => object(Cake\ORM\Entity) {}, (int) 6 => object(Cake\ORM\Entity) {}, (int) 7 => object(Cake\ORM\Entity) {}, (int) 8 => object(Cake\ORM\Entity) {}, (int) 9 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 29023 $metaTitle = 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee' $metaKeywords = 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population' $metaDesc = ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...' $disp = '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />&quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'</pre><pre class="stack-trace">include - APP/Template/Layout/printlayout.ctp, line 8 Cake\View\View::_evaluate() - CORE/src/View/View.php, line 1413 Cake\View\View::_render() - CORE/src/View/View.php, line 1374 Cake\View\View::renderLayout() - CORE/src/View/View.php, line 927 Cake\View\View::render() - CORE/src/View/View.php, line 885 Cake\Controller\Controller::render() - CORE/src/Controller/Controller.php, line 791 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 126 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51</pre></div></pre>latest-news-updates/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077.html"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <link href="https://im4change.in/css/control.css" rel="stylesheet" type="text/css" media="all"/> <title>LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee | Im4change.org</title> <meta name="description" content=" -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are..."/> <script src="https://im4change.in/js/jquery-1.10.2.js"></script> <script type="text/javascript" src="https://im4change.in/js/jquery-migrate.min.js"></script> <script language="javascript" type="text/javascript"> $(document).ready(function () { var img = $("img")[0]; // Get my img elem var pic_real_width, pic_real_height; $("<img/>") // Make in memory copy of image to avoid css issues .attr("src", $(img).attr("src")) .load(function () { pic_real_width = this.width; // Note: $(this).width() will not pic_real_height = this.height; // work for in memory images. }); }); </script> <style type="text/css"> @media screen { div.divFooter { display: block; } } @media print { .printbutton { display: none !important; } } </style> </head> <body> <table cellpadding="0" cellspacing="0" border="0" width="98%" align="center"> <tr> <td class="top_bg"> <div class="divFooter"> <img src="https://im4change.in/images/logo1.jpg" height="59" border="0" alt="Resource centre on India's rural distress" style="padding-top:14px;"/> </div> </td> </tr> <tr> <td id="topspace"> </td> </tr> <tr id="topspace"> <td> </td> </tr> <tr> <td height="50" style="border-bottom:1px solid #000; padding-top:10px;" class="printbutton"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> <tr> <td width="100%"> <h1 class="news_headlines" style="font-style:normal"> <strong>Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee</strong></h1> </td> </tr> <tr> <td width="100%" style="font-family:Arial, 'Segoe Script', 'Segoe UI', sans-serif, serif"><font size="3"> <div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />"It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div> </font> </td> </tr> <tr> <td> </td> </tr> <tr> <td height="50" style="border-top:1px solid #000; border-bottom:1px solid #000;padding-top:10px;"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> </table></body> </html>' } $reasonPhrase = 'OK'header - [internal], line ?? Cake\Http\ResponseEmitter::emitStatusLine() - CORE/src/Http/ResponseEmitter.php, line 148 Cake\Http\ResponseEmitter::emit() - CORE/src/Http/ResponseEmitter.php, line 54 Cake\Http\Server::emit() - CORE/src/Http/Server.php, line 141 [main] - ROOT/webroot/index.php, line 39
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'' : 'none');"><b>Notice</b> (8)</a>: Undefined variable: urlPrefix [<b>APP/Template/Layout/printlayout.ctp</b>, line <b>8</b>]<div id="cakeErr6815bc37e08cf-trace" class="cake-stack-trace" style="display: none;"><a href="javascript:void(0);" onclick="document.getElementById('cakeErr6815bc37e08cf-code').style.display = (document.getElementById('cakeErr6815bc37e08cf-code').style.display == 'none' ? '' : 'none')">Code</a> <a href="javascript:void(0);" onclick="document.getElementById('cakeErr6815bc37e08cf-context').style.display = (document.getElementById('cakeErr6815bc37e08cf-context').style.display == 'none' ? '' : 'none')">Context</a><pre id="cakeErr6815bc37e08cf-code" class="cake-code-dump" style="display: none;"><code><span style="color: #000000"><span style="color: #0000BB"></span><span style="color: #007700"><</span><span style="color: #0000BB">head</span><span style="color: #007700">> </span></span></code> <span class="code-highlight"><code><span style="color: #000000"> <link rel="canonical" href="<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">Configure</span><span style="color: #007700">::</span><span style="color: #0000BB">read</span><span style="color: #007700">(</span><span style="color: #DD0000">'SITE_URL'</span><span style="color: #007700">); </span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$urlPrefix</span><span style="color: #007700">;</span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">category</span><span style="color: #007700">-></span><span style="color: #0000BB">slug</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>/<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">seo_url</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>.html"/> </span></code></span> <code><span style="color: #000000"><span style="color: #0000BB"> </span><span style="color: #007700"><</span><span style="color: #0000BB">meta http</span><span style="color: #007700">-</span><span style="color: #0000BB">equiv</span><span style="color: #007700">=</span><span style="color: #DD0000">"Content-Type" </span><span style="color: #0000BB">content</span><span style="color: #007700">=</span><span style="color: #DD0000">"text/html; charset=utf-8"</span><span style="color: #007700">/> </span></span></code></pre><pre id="cakeErr6815bc37e08cf-context" class="cake-context" style="display: none;">$viewFile = '/home/brlfuser/public_html/src/Template/Layout/printlayout.ctp' $dataForView = [ 'article_current' => object(App\Model\Entity\Article) { 'id' => (int) 29023, 'title' => 'Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'subheading' => '', 'description' => '<div align="justify"> -Business Standard<br /> <br /> <em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /> </em><br /> As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /> <br /> In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> &quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 29023, 'metaTitle' => 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'metaKeywords' => 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population', 'metaDesc' => ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...', 'disp' => '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />&quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 29023, 'title' => 'Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'subheading' => '', 'description' => '<div align="justify"> -Business Standard<br /> <br /> <em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /> </em><br /> As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /> <br /> In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> &quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {}, (int) 1 => object(Cake\ORM\Entity) {}, (int) 2 => object(Cake\ORM\Entity) {}, (int) 3 => object(Cake\ORM\Entity) {}, (int) 4 => object(Cake\ORM\Entity) {}, (int) 5 => object(Cake\ORM\Entity) {}, (int) 6 => object(Cake\ORM\Entity) {}, (int) 7 => object(Cake\ORM\Entity) {}, (int) 8 => object(Cake\ORM\Entity) {}, (int) 9 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 29023 $metaTitle = 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee' $metaKeywords = 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population' $metaDesc = ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...' $disp = '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />&quot;It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators,&quot; said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. &quot;There have also been some questions over the verification process of urban data, which is why it is taking time to be released,&quot; said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'</pre><pre class="stack-trace">include - APP/Template/Layout/printlayout.ctp, line 8 Cake\View\View::_evaluate() - CORE/src/View/View.php, line 1413 Cake\View\View::_render() - CORE/src/View/View.php, line 1374 Cake\View\View::renderLayout() - CORE/src/View/View.php, line 927 Cake\View\View::render() - CORE/src/View/View.php, line 885 Cake\Controller\Controller::render() - CORE/src/Controller/Controller.php, line 791 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 126 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51</pre></div></pre>latest-news-updates/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077.html"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <link href="https://im4change.in/css/control.css" rel="stylesheet" type="text/css" media="all"/> <title>LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee | Im4change.org</title> <meta name="description" content=" -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are..."/> <script src="https://im4change.in/js/jquery-1.10.2.js"></script> <script type="text/javascript" src="https://im4change.in/js/jquery-migrate.min.js"></script> <script language="javascript" type="text/javascript"> $(document).ready(function () { var img = $("img")[0]; // Get my img elem var pic_real_width, pic_real_height; $("<img/>") // Make in memory copy of image to avoid css issues .attr("src", $(img).attr("src")) .load(function () { pic_real_width = this.width; // Note: $(this).width() will not pic_real_height = this.height; // work for in memory images. }); }); </script> <style type="text/css"> @media screen { div.divFooter { display: block; } } @media print { .printbutton { display: none !important; } } </style> </head> <body> <table cellpadding="0" cellspacing="0" border="0" width="98%" align="center"> <tr> <td class="top_bg"> <div class="divFooter"> <img src="https://im4change.in/images/logo1.jpg" height="59" border="0" alt="Resource centre on India's rural distress" style="padding-top:14px;"/> </div> </td> </tr> <tr> <td id="topspace"> </td> </tr> <tr id="topspace"> <td> </td> </tr> <tr> <td height="50" style="border-bottom:1px solid #000; padding-top:10px;" class="printbutton"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> <tr> <td width="100%"> <h1 class="news_headlines" style="font-style:normal"> <strong>Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee</strong></h1> </td> </tr> <tr> <td width="100%" style="font-family:Arial, 'Segoe Script', 'Segoe UI', sans-serif, serif"><font size="3"> <div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />"It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div> </font> </td> </tr> <tr> <td> </td> </tr> <tr> <td height="50" style="border-top:1px solid #000; border-bottom:1px solid #000;padding-top:10px;"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> </table></body> </html>' } $cookies = [] $values = [ (int) 0 => 'text/html; charset=UTF-8' ] $name = 'Content-Type' $first = true $value = 'text/html; charset=UTF-8'header - [internal], line ?? 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This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> "It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 29023, 'metaTitle' => 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'metaKeywords' => 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population', 'metaDesc' => ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...', 'disp' => '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />"It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 29023, 'title' => 'Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee', 'subheading' => '', 'description' => '<div align="justify"> -Business Standard<br /> <br /> <em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /> </em><br /> As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /> <br /> In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /> <br /> Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /> <br /> The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /> <br /> To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /> <br /> "It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /> <br /> The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official.<br /> <br /> The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /> <br /> These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /> <br /> The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /> <br /> This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /> <br /> The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /> <br /> Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /> <br /> However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /> <br /> In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /> <br /> In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /> <br /> The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /> <br /> The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. </div>', 'credit_writer' => 'Business Standard, 26 August, 2015, http://www.business-standard.com/article/economy-policy/centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-115082600060_1.html', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'centre-may-appoint-panel-under-niti-aayog-to-review-urban-census-sanjeeb-mukherjee-4677077', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 4677077, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {}, (int) 1 => object(Cake\ORM\Entity) {}, (int) 2 => object(Cake\ORM\Entity) {}, (int) 3 => object(Cake\ORM\Entity) {}, (int) 4 => object(Cake\ORM\Entity) {}, (int) 5 => object(Cake\ORM\Entity) {}, (int) 6 => object(Cake\ORM\Entity) {}, (int) 7 => object(Cake\ORM\Entity) {}, (int) 8 => object(Cake\ORM\Entity) {}, (int) 9 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 29023 $metaTitle = 'LATEST NEWS UPDATES | Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee' $metaKeywords = 'homeless,multidimensional poverty,Deprivation,socio economic and caste census,socio economic caste census,SECC,SECC 2011,NITI Aayog,Housing,Homeless Population' $metaDesc = ' -Business Standard The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are...' $disp = '<div align="justify">-Business Standard<br /><br /><em>The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable<br /></em><br />As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes.<br /><br />In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India.<br /><br />Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes.<br /><br />The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census.<br /><br />To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC).<br /><br />"It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third.<br /><br />The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official.<br /><br />The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc.<br /><br />These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill.<br /><br />The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable.<br /><br />This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived.<br /><br />The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural.<br /><br />Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen.<br /><br />However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government.<br /><br />In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded.<br /><br />In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list.<br /><br />The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection.<br /><br />The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle.</div>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'
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Centre may appoint panel under NITI Aayog to review urban census -Sanjeeb Mukherjee |
-Business Standard
The yet-to-be released census shows 27.65 per cent of 63.4 million households to be highly vulnerable As much as 27.65 per cent of the 63.4 million urban households in India are either homeless or are occupationally/socially vulnerable and, hence, are likely to be automatically included in a list of beneficiaries for government programmes. In contrast, the figure for rural India is 0.92 per cent of 179.1 million households, according to the census for rural India released earlier. This shows there is a vast divergence between the people who are to be automatically included in the list of vulnerable people in rural and urban India. Although this divergence can be attributed to the difference in approach and methodology in collating and interpreting data, it could be a nightmare for the policy makers and others seeking to use the data for prioritising the beneficiaries under various government schemes. The unreleased data for urban India show a higher number of people to be automatically included though the total number of households enumerated is less than the rural census. To look at all these inconsistencies between the two data sets, the Centre is expected to constitute a committee headed by NITI Aayog Vice-Chairman Arvind Panagariya on the urban socio-economic caste census (SECC). "It is not possible to redo the entire urban census as it will be time-consuming. What we can do is to use the same set of questions to review the automatic inclusion criteria, or try and bring about some consistency between the indicators," said a senior official. Panagariya already heads a panel on poverty elimination and caste census. This one is the expected to be the third. The official said that unless there was some similarity between the two sets of numbers, it would be difficult for the government to go ahead with its planned objective of better targeting the poor for social programmes through these numbers. "There have also been some questions over the verification process of urban data, which is why it is taking time to be released," said the official. The findings for urban India showed 27.65 per cent of urban India comprises those who are homeless or reside in shanties, which are made of plastic sheets, grass, thatch, bamboo, mud, unburnt brick, etc. These also include households that do not have any income from any source, or is engaged in begging or rag picking. There are also households with all members aged between 18 and 60 years either have a disability or are chronically ill. The SECC for urban India, which was done alongside the SECC for rural India, was based on the parameters and indicators as suggested by a committee headed by S R Hashim of the erstwhile Planning Commission. It ranked those households which are not automatically included or excluded on a scale of one to 12, where 12 is most vulnerable and is the closest to being automatically included while those in the 1-4 grade are the least vulnerable. This methodology showed that if the households that are ranked 4-12 are added to the list of automatically included, which is 27.65 per cent, an urban poverty number close to 35 per cent of the 63 million surveyed was derived. The indicators adopted by SECC urban for arriving at its automatic exclusion number or the automatic inclusion numbers is also vastly different and inconsistent with the rural. Officials said the SECC for rural India was based on robust approach and was according to the method suggested by former member of National Advisory Council N C Saxena and thereafter analysed by former Planning Commission member Abhijit Sen. However, in the case of urban SECC, the data was collected based on the suggestions and methodology of the Hashim report, though the report was not formally accepted by the government. In the SECC for rural areas, 39.39 per cent of the 179.1 million rural households were automatically excluded, while in the urban census 31.23 per cent of the 63.4 million urban households were automatically excluded. In other words, 70.5 million of rural households were not included, while 19.7 million of urban households were automatically excluded from the list. The urban SECC showed that 13.37 per cent of the 63.4 million urban households have a dwelling unit of four rooms or more with walls made of brick or stone and concrete roof. Almost 11.56 per cent of the total urban households have any one of the following assets: four-wheeler, air conditioner, and computer or laptop with internet connection. The data also showed that 6.29 per cent of the 63.4 million urban households have any three or more of refrigerator, landline, washing machine or two-wheeler motorised vehicle. |