{"id":480,"date":"2013-04-01T18:36:45","date_gmt":"2013-04-01T18:36:45","guid":{"rendered":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/?p=480"},"modified":"2013-04-01T18:36:46","modified_gmt":"2013-04-01T18:36:46","slug":"demographic-bits-and-bytes","status":"publish","type":"post","link":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/2013\/04\/01\/demographic-bits-and-bytes\/","title":{"rendered":"Demographic bits and bytes"},"content":{"rendered":"<p>The Census Bureau records quite numerous useful data beyond demographics here in the US. Included below are some examples, provided by the US Census Bureau, that exemplify just how informative some of this data can actually be!<\/p>\n<p><span style=\"text-decoration: underline\"><strong>Schools<\/strong><\/span><\/p>\n<p><strong><a title=\"this working paper\" href=\"http:\/\/www.census.gov\/hhes\/school\/files\/ewert_private_school_enrollment.pdf\">This working paper <\/a><\/strong>discusses the decline in attendance at private schools over the past decade. According to the census bureau:<\/p>\n<blockquote><p>Data from several surveys, including the Current Population Survey and American Community Survey, show a decline in private school enrollment over the last decade. The working paper compares trends across datasets and subgroups and explores possible underlying causes of the decline in enrollment, which occurred particularly at larger, religiously affiliated schools in cities and suburbs. Possible causes explored by the paper include the growth in charter schools, home schooling and the recession.<\/p>\n<p>&nbsp;<\/p><\/blockquote>\n<p><span style=\"text-decoration: underline\"><strong>Disability, Employment, and Government Assistance<br \/>\n<\/strong><\/span><\/p>\n<p>The Census Bureau also <span style=\"text-decoration: underline\"><strong><a title=\"reports\" href=\"http:\/\/www.census.gov\/prod\/2013pubs\/acsbr11-12.pdf\">reports<\/a><\/strong><\/span> that workers with a disability are less likely to be employed and for those who are employed, are more likely to hold jobs with lower earnings. The three most common occupations for men with disabilities were drivers\/sales workers and truck drivers (246,000); janitors and building cleaners (217,000); and laborers and freight, stock, and material movers (171,000). For women, as cashiers (195,000); secretaries or administrative assistants (189,000); and nursing, psychiatric or home health aides (172,000). These data can be found on the Census website under the Disability Employment Tabulation available through <strong><a title=\"American Factfinder\" href=\"http:\/\/factfinder2.census.gov\/faces\/nav\/jsf\/pages\/searchresults.xhtml?refresh=t\">American Factfinder. <\/a><\/strong><\/p>\n<p style=\"text-align: left\"><a href=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/DisabilityGraph.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-483 aligncenter\" alt=\"DisabilityGraph\" src=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/DisabilityGraph-300x214.jpg\" width=\"300\" height=\"214\" \/><\/a>The report, which uses data from 2011, indicates that 30% of of the 46 million adults that receive government assistance have a disability of some kind. There is a relationship to these statistics and those regarding employment as well; Bernice Boursiquot, co-author of the report and Census Bureau statistician noted that &#8220;On average, people with disabilities have lower employment and earnings; therefore, understanding what assistance people with disabilities receive may help governments better coordinate and administer their programs.&#8221;<\/p>\n<p style=\"text-align: left\"><a href=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/DisabilityandAssistance.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-medium wp-image-505\" alt=\"DisabilityandAssistance\" src=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/DisabilityandAssistance-300x225.jpg\" width=\"300\" height=\"225\" \/><\/a><\/p>\n<p><span style=\"text-decoration: underline\"><strong>Demographics &amp; Income<\/strong><\/span><\/p>\n<p>And if you were wondering about demographics and income, the Bureau has also released income\/earnings estimates for the third quarter (July-September) of 2011 by selected demographic characteristics such as gender, age, race\/ethnicity, martial status, and educational attainment. Tables are available here:<\/p>\n<ul>\n<li><strong>Income: <a href=\"http:\/\/www.census.gov\/sipp\/tables\/quarterly-est\/income\/income-11.html\">http:\/\/www.census.gov\/sipp\/tables\/quarterly-est\/income\/income-11.html<\/a><\/strong><\/li>\n<li><strong>Earnings: <a href=\"http:\/\/www.census.gov\/sipp\/tables\/quarterly-est\/earnings\/earnings-11.html\">http:\/\/www.census.gov\/sipp\/tables\/quarterly-est\/earnings\/earnings-11.html<\/a><\/strong><\/li>\n<\/ul>\n<p>A <strong><a title=\"different report\" href=\"http:\/\/www.census.gov\/prod\/2013pubs\/acsbr11-23.pdf\">different report<\/a><\/strong>, released Feb 11 shows that the Bridgeport-Stamford-Norwalk, CT metropolitan area near NYC has the highest percentage of households with high income <strong>in the nation<\/strong> at 17.9 percent. High income is defined as being in the top 5 percent of national income distribution, which is an annual household income of at least $191,469.<\/p>\n<p><span style=\"text-decoration: underline\"><strong>Megacommuters<\/strong><\/span><\/p>\n<p>How long is your commute to work? How many miles do you usually drive? The ACS (American Community Survey) collects and provides this information. See ACS report\u00a0 <strong><a title=\"here\" href=\"http:\/\/www.census.gov\/newsroom\/releases\/pdf\/acs_20_out_of_state_and_long_commutes_report.pdfhttp:\/\/\">here<\/a>\u00a0<\/strong>by Brian McKenzie, a Census Bureau statistician, to see how you compare to the rest of the US workforce. As an example, about 342,000 workers commute <strong>into<\/strong> Suffolk County, Massachusetts (Boston area) every day from outside of that county; if you&#8217;ve ever driven on I-93 or I-95 at rush hour, it certainly seems like it makes sense!<\/p>\n<p style=\"text-align: left\"><a href=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/Megacommuting.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter  wp-image-492\" alt=\"Megacommuting\" src=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/Megacommuting.jpg\" width=\"533\" height=\"363\" \/><\/a>Did you know that:<\/p>\n<ul>\n<li>600,000 people in the US travel 90 minutes and 50 miles to work; 10.8 million travel an hour each way.<\/li>\n<li>8.1 percent of US workers have commutes of 60 minutes or longer<\/li>\n<li>4.3 percent walk from home<\/li>\n<li>The <strong>average<\/strong> one-way daily commute for workers across the country is <strong>25.5 minutes<\/strong>.<\/li>\n<li>Of those who were classified as &#8220;megacommuters&#8221;,\u00a0 75.4 percent were male and 24.6 percent were female.<\/li>\n<\/ul>\n<p>For more information about Megacommuting in the US, see the below links:<\/p>\n<ul>\n<li><a title=\"Poster\" href=\"http:\/\/www.census.gov\/newsroom\/releases\/pdf\/poster_megacommuting_in_the_u.s.pdf\">Poster<\/a><\/li>\n<li><a title=\"Paper\" href=\"http:\/\/www.census.gov\/newsroom\/releases\/pdf\/paper_mega_%20commuters_us.pdf\">Paper<\/a><\/li>\n<\/ul>\n<p><span style=\"text-decoration: underline\"><strong>Home-based workers<\/strong><\/span><\/p>\n<p>Working at home is on the rise! In contrast to megacommuting, it is now apparent that more and more individuals are choosing to work from home. The Census Bureau has also compiled an<strong><a title=\"infographic\" href=\"http:\/\/www.census.gov\/how\/infographics\/home_based_workers.html\"> infographic<\/a><\/strong> to dissect some of the statistics involved with this phenomenon.<\/p>\n<div id=\"attachment_502\" style=\"width: 522px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/Workhome_snip.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-502\" class=\"size-full wp-image-502\" alt=\"Snippet from infographic\" src=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/files\/2013\/03\/Workhome_snip.jpg\" width=\"512\" height=\"436\" \/><\/a><p id=\"caption-attachment-502\" class=\"wp-caption-text\">Snippet from infographic<\/p><\/div>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>The Census Bureau records quite numerous useful data beyond demographics here in the US. Included below are some examples, provided by the US Census Bureau, that exemplify just how informative some of this data can actually be! Schools This working &hellip; <a href=\"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/2013\/04\/01\/demographic-bits-and-bytes\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":74,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[42,185,232],"tags":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9NL4O-7K","_links":{"self":[{"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/posts\/480"}],"collection":[{"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/users\/74"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/comments?post=480"}],"version-history":[{"count":6,"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/posts\/480\/revisions"}],"predecessor-version":[{"id":546,"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/posts\/480\/revisions\/546"}],"wp:attachment":[{"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/media?parent=480"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/categories?post=480"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.lib.uconn.edu\/outsidetheneatline\/wp-json\/wp\/v2\/tags?post=480"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}