No Diego Costa for Spain

first_imgMADRID (AP):Spain coach Vicente del Bosque yesterday left Diego Costa out of the squad for the team’s last two qualifying matches for next year’s European Championship.Costa has a one-match suspension for an accumulation of yellow cards and was not eligible for the first game against Luxembourg on October 9.Del Bosque said, “We have preferred not to include him” just for the second match against Ukraine.”He’s not playing badly,” Del Bosque said of Costa, adding that Spain would “count on him in the future, if everything goes normally”.Costa is also serving a three-match ban in England for violent conduct during Chelsea’s 2-0 win over Arsenal after putting his hands in the face of defender Laurent Koscielny.”I did not like what I saw,” Del Bosque said of that incident. “I did not like what he (Costa) did, of course not.”With AndrÈs Iniesta and Jorge “Koke” ResurrecciÛn out injured, Del Bosque included Thiago Alcantara, Bruno Soriano, Inigo MartÌnez, Manuel “Nolito” Agudo, and Alvaro Morata in the squad.Chelsea forward Pedro Rodriguez is included to bolster Spain’s attack.Goalkeeper Iker Casillas is also in the squad, alongside Manchester’s David De Gea and Sergio Rico of Sevilla.Spain top Group C and can clinch qualification with a win against Luxembourg.Spain:Goalkeepers: Iker Casillas (FC Porto), David de Gea (Manchester United), Sergio Rico (Sevilla).Defenders: Marc Bartra (Barcelona), Juanfran Torres (AtlÈtico Madrid), Sergio Ramos (Real Madrid), Jordi Alba (Barcelona), Gerard Pique (Barcelona), Dani Carvajal (Real Madrid), Cesar Azpilicueta (Chelsea), Inigo Martinez (Real Sociedad).Midfielders: Sergio Busquets (Barcelona), Isco Alarcon (Real Madrid), Cesc Fabregas (Chelsea), Santi Cazorla (Arsenal), David Silva (Manchester City), Thiago Alcantara (Bayern Munich), Juan Mata (Manchester United), Bruno Soriano (Villarreal).Forwards: Pedro Rodriguez (Chelsea), Paco Alcacer (Valencia), Alvaro Morata (Juventus), Manuel “Nolito” Agudo (Celta Vigo).last_img read more

What Surveys Have Told Us About U.S. Social Mobility

first_imgIt’s Already on File: How Administrative Records Can Help Assess Mobility Last summer, some 30 experts gathered at the National Academy of Sciences in Washington, D.C., to discuss whether the government should design and carry out the first survey in 40 years of social mobility in the United States. The researchers agreed that it was important to document the massive changes that had taken place in the U.S. economy since the last similar study in 1973. And nobody knew better the potential value of such surveys than Robert Hauser, the man who convened the 1-day meeting.Now head of the National Research Council’s Division of Behavioral and Social Sciences and Education, Hauser had teamed up 4 decades ago with a colleague at the University of Wisconsin, Madison, David Featherman, to ask about 33,500 adult men what type of work they and their fathers had done. They were replicating a first-ever survey of U.S. economic mobility done in 1962, using a larger and more diverse sample to get a glimpse into how economic mobility had changed after the social upheavals of the 1960s. Both surveys, called the Occupational Changes in a Generation (OCG), had added income-related questions to an ongoing government survey of households that provides monthly unemployment figures.The results were both expected and eye-opening. The 1962 survey “found substantial upward mobility,” according to a 1977 description of the research in a university newsletter, and that schooling was the dominant factor in determining their career path. At the same time, it noted, “self-employed professionals, proprietors, and farmers” were much more likely to have had fathers in the same professions than did peers holding lower level white collar and blue-collar jobs.Sign up for our daily newsletterGet more great content like this delivered right to you!Country *AfghanistanAland IslandsAlbaniaAlgeriaAndorraAngolaAnguillaAntarcticaAntigua and BarbudaArgentinaArmeniaArubaAustraliaAustriaAzerbaijanBahamasBahrainBangladeshBarbadosBelarusBelgiumBelizeBeninBermudaBhutanBolivia, Plurinational State ofBonaire, Sint Eustatius and SabaBosnia and HerzegovinaBotswanaBouvet IslandBrazilBritish Indian Ocean TerritoryBrunei DarussalamBulgariaBurkina FasoBurundiCambodiaCameroonCanadaCape VerdeCayman IslandsCentral African RepublicChadChileChinaChristmas IslandCocos (Keeling) IslandsColombiaComorosCongoCongo, The Democratic Republic of theCook IslandsCosta RicaCote D’IvoireCroatiaCubaCuraçaoCyprusCzech RepublicDenmarkDjiboutiDominicaDominican RepublicEcuadorEgyptEl SalvadorEquatorial GuineaEritreaEstoniaEthiopiaFalkland Islands (Malvinas)Faroe IslandsFijiFinlandFranceFrench GuianaFrench PolynesiaFrench Southern TerritoriesGabonGambiaGeorgiaGermanyGhanaGibraltarGreeceGreenlandGrenadaGuadeloupeGuatemalaGuernseyGuineaGuinea-BissauGuyanaHaitiHeard Island and Mcdonald IslandsHoly See (Vatican City State)HondurasHong KongHungaryIcelandIndiaIndonesiaIran, Islamic Republic ofIraqIrelandIsle of ManIsraelItalyJamaicaJapanJerseyJordanKazakhstanKenyaKiribatiKorea, Democratic People’s Republic ofKorea, Republic ofKuwaitKyrgyzstanLao People’s Democratic RepublicLatviaLebanonLesothoLiberiaLibyan Arab JamahiriyaLiechtensteinLithuaniaLuxembourgMacaoMacedonia, The Former Yugoslav Republic ofMadagascarMalawiMalaysiaMaldivesMaliMaltaMartiniqueMauritaniaMauritiusMayotteMexicoMoldova, Republic ofMonacoMongoliaMontenegroMontserratMoroccoMozambiqueMyanmarNamibiaNauruNepalNetherlandsNew CaledoniaNew ZealandNicaraguaNigerNigeriaNiueNorfolk IslandNorwayOmanPakistanPalestinianPanamaPapua New GuineaParaguayPeruPhilippinesPitcairnPolandPortugalQatarReunionRomaniaRussian FederationRWANDASaint Barthélemy Saint Helena, Ascension and Tristan da CunhaSaint Kitts and NevisSaint LuciaSaint Martin (French part)Saint Pierre and MiquelonSaint Vincent and the GrenadinesSamoaSan MarinoSao Tome and PrincipeSaudi ArabiaSenegalSerbiaSeychellesSierra LeoneSingaporeSint Maarten (Dutch part)SlovakiaSloveniaSolomon IslandsSomaliaSouth AfricaSouth Georgia and the South Sandwich IslandsSouth SudanSpainSri LankaSudanSurinameSvalbard and Jan MayenSwazilandSwedenSwitzerlandSyrian Arab RepublicTaiwanTajikistanTanzania, United Republic ofThailandTimor-LesteTogoTokelauTongaTrinidad and TobagoTunisiaTurkeyTurkmenistanTurks and Caicos IslandsTuvaluUgandaUkraineUnited Arab EmiratesUnited KingdomUnited StatesUruguayUzbekistanVanuatuVenezuela, Bolivarian Republic ofVietnamVirgin Islands, BritishWallis and FutunaWestern SaharaYemenZambiaZimbabweI also wish to receive emails from AAAS/Science and Science advertisers, including information on products, services and special offers which may include but are not limited to news, careers information & upcoming events.Required fields are included by an asterisk(*)But these findings held only for whites. Young African-American males tended to hold low-status jobs even if their fathers were white-collar workers, and regardless of how far they had gone in school. The study showed “substantial evidence of cumulative discrimination against blacks” that was not affected by education or background.The 1973 follow-up survey found that mobility patterns had begun to converge for blacks and whites. Education appeared to play a bigger role than before in determining the type of job held by African-American men compared with their white counterparts. But ironically, there was also “increased inequality of opportunity” within the African-American population, as they were now much more likely than a decade ago to hold jobs similar to their father’s occupation.For all their insights, however, the OCG surveys came with some important caveats. Jobs represent only one dimension of social mobility, for instance, and each study was a one-shot affair, capturing subjects at a particular moment in time. The surveys also excluded women.Researchers have been able to commandeer a different, and ongoing, U.S. survey to fill in some of those gaps. In 1968, the government decided to monitor the impact of various programs that were part of President Lyndon Johnson’s War on Poverty. Although trimmed and revised over the years, the Panel Study of Income Dynamics (PSID) remains one of the best ongoing collection of longitudinal data on various socioeconomic and health trends.The most recent PSID analysis, done in 2012 by a consortium of researchers who are part of the Pew Economic Mobility Project, found that college graduates are five times more likely to move from the bottom rungs to the middle of the economic ladder than those without degrees. Whites are twice as likely as blacks to make such a move. And overall, some 43% of children from families in the lower rungs remain there as adults.But the picture that PSID paints of social mobility is still very blurry and incomplete. Its sample is skewed toward the low-income households originally targeted by the antipoverty programs, and the size of that core sample was cut by two-thirds in 1996 after budget cuts to the federal agencies that fund the University of Michigan to carry out the survey.There are other government-funded surveys that have also contributed to our knowledge of social mobility. Since 1984, the Census Bureau’s Survey of Income and Program Participation has gathered data on how government programs affect income and wealth. And the General Social Survey (GSS), funded since 1972 by the National Science Foundation and conducted by the University of Chicago, measures intergenerational educational and occupational mobility among small samples. But GSS doesn’t track income mobility.So where do things stand? Participants at the National Academy’s workshop discussed several options for gathering better data, but all had serious flaws. A start-from-scratch survey would allow researchers to cover the most bases, everyone agreed, but the chances of persuading Congress to pay for a survey large enough to provide meaningful results are almost nil. Piggybacking onto an existing vehicle, like the Census Bureau’s American Community Survey, would lower the cost significantly, but its scope would have to be severely limited.Many experts believe the most promising approach may be making greater use of administrative records, the massive volume of information that government agencies already collect for other purposes. The cost would be minimal. However, that approach will once more require researchers to be creative about piecing together data from many sources to create a complete picture of U.S. social mobility.See also:The science of inequality How Two Economists Got Direct Access to IRS Tax Recordscenter_img The IGE: Anatomy of a Mobility Scorelast_img read more