IF 4.5

Socius Pub Date : 2020-01-01 Epub Date: 2020-04-23 DOI: 10.1177/2378023120918082

John Robert Warren, Chandra Muller, Robert A Hummer, Eric Grodsky, Melissa Humphries

{"title":"Which Aspects of Education Matter for Early Adult Mortality? Evidence from the High School and Beyond Cohort.","authors":"John Robert Warren, Chandra Muller, Robert A Hummer, Eric Grodsky, Melissa Humphries","doi":"10.1177/2378023120918082","DOIUrl":"10.1177/2378023120918082","url":null,"abstract":"What dimensions of education matter for people's chances of surviving young adulthood? Do cognitive skills, non-cognitive skills, course taking patterns, and school social contexts matter for young adult mortality, even net of educational attainment? We analyze data from High School & Beyond-a nationally representative cohort of ~25,000 high school students first interviewed in 1980. Many dimensions of education are associated with young adult mortality, and high school students' math course taking retain their associations with mortality net of educational attainment. Our work draws on theories and measures from sociological and educational research and enriches public health, economic, and demographic research on educational gradients in mortality that has almost exclusively relied on ideas of human capital accumulation and measures of degree attainment. Our findings also call on social and education researchers to engage together in research on the life-long consequences of educational processes, school structures, and inequalities in opportunities to learn.","PeriodicalId":36345,"journal":{"name":"Socius","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575125/pdf/nihms-1572659.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38624014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Expensive Childcare and Short School Days = Lower Maternal Employment and More Time in Childcare? Evidence from the American Time Use Survey. 昂贵的育儿费用和较短的上学时间=更低的母亲就业率和更多的育儿时间?来自美国时间使用调查的证据。

IF 4.5

Socius Pub Date : 2019-01-01 Epub Date: 2019-07-29 DOI: 10.1177/2378023119860277

Leah Ruppanner, Stephanie Moller, Liana Sayer

{"title":"Expensive Childcare and Short School Days = Lower Maternal Employment and More Time in Childcare? Evidence from the American Time Use Survey.","authors":"Leah Ruppanner, Stephanie Moller, Liana Sayer","doi":"10.1177/2378023119860277","DOIUrl":"https://doi.org/10.1177/2378023119860277","url":null,"abstract":"This study investigates the relationship between maternal employment and state-to-state differences in childcare cost and mean school day length. Pairing state-level measures with an individual-level sample of prime working-age mothers from the American Time Use Survey (2005-2014; n = 37,993), we assess the multilevel and time-varying effects of childcare costs and school day length on maternal full-time and part-time employment and childcare time. We find mothers' odds of full-time employment are lower and part-time employment higher in states with expensive childcare and shorter school days. Mothers spend more time caring for children in states where childcare is more expensive and as childcare costs increase. Our results suggest that expensive childcare and short school days are important barriers to maternal employment and, for childcare costs, result in greater investments in childcare time. Politicians engaged in national debates about federal childcare policies should look to existing state childcare structures for policy guidance.","PeriodicalId":36345,"journal":{"name":"Socius","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/2378023119860277","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39000787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 37

Improving Metadata Infrastructure for Complex Surveys: Insights from the Fragile Families Challenge. 改善复杂调查的元数据基础设施：来自脆弱家庭挑战的见解。

IF 4.5

Socius Pub Date : 2019-01-01 Epub Date: 2019-09-10 DOI: 10.1177/2378023118817378

Alexander T Kindel, Vineet Bansal, Kristin D Catena, Thomas H Hartshorne, Kate Jaeger, Dawn Koffman, Sara McLanahan, Maya Phillips, Shiva Rouhani, Ryan Vinh, Matthew J Salganik

{"title":"Improving Metadata Infrastructure for Complex Surveys: Insights from the Fragile Families Challenge.","authors":"Alexander T Kindel, Vineet Bansal, Kristin D Catena, Thomas H Hartshorne, Kate Jaeger, Dawn Koffman, Sara McLanahan, Maya Phillips, Shiva Rouhani, Ryan Vinh, Matthew J Salganik","doi":"10.1177/2378023118817378","DOIUrl":"10.1177/2378023118817378","url":null,"abstract":"Researchers rely on metadata systems to prepare data for analysis. As the complexity of data sets increases and the breadth of data analysis practices grow, existing metadata systems can limit the efficiency and quality of data preparation. This article describes the redesign of a metadata system supporting the Fragile Families and Child Wellbeing Study on the basis of the experiences of participants in the Fragile Families Challenge. The authors demonstrate how treating metadata as data (i.e., releasing comprehensive information about variables in a format amenable to both automated and manual processing) can make the task of data preparation less arduous and less error prone for all types of data analysis. The authors hope that their work will facilitate new applications of machine-learning methods to longitudinal surveys and inspire research on data preparation in the social sciences. The authors have open-sourced the tools they created so that others can use and improve them.","PeriodicalId":36345,"journal":{"name":"Socius","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/7f/fa/nihms-1847416.PMC10198672.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9503235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Job Characteristics, Job Preferences, and Physical and Mental Health in Later Life. 职业特征、职业偏好与晚年身心健康。

IF 4.5

Socius Pub Date : 2019-01-01 Epub Date: 2019-04-03 DOI: 10.1177/2378023119836003

Jessica Halliday Hardie, Jonathan Daw, S Michael Gaddis

引用次数: 1

Introduction to the Special Collection on the Fragile Families Challenge. 关于脆弱家庭挑战的特别收藏介绍。

IF 3

Socius Pub Date : 2019-01-01 Epub Date: 2019-09-10 DOI: 10.1177/2378023119871580

Matthew J Salganik, Ian Lundberg, Alexander T Kindel, Sara McLanahan

引用次数: 0

Women's Assessments of Gender Equality. 妇女对性别平等的评估。

IF 4.5

Socius Pub Date : 2019-01-01 Epub Date: 2019-09-04 DOI: 10.1177/2378023119872387

Charles Kurzman, Willa Dong, Brandon Gorman, Karam Hwang, Renee Ryberg, Batool Zaidi

引用次数: 0

Humans in the Loop: Incorporating Expert and Crowd-Sourced Knowledge for Predictions Using Survey Data. 循环中的人类：利用调查数据结合专家和众包知识进行预测。

IF 4.5

Socius Pub Date : 2019-01-01 Epub Date: 2019-09-10 DOI: 10.1177/2378023118820157

Anna Filippova, Connor Gilroy, Ridhi Kashyap, Antje Kirchner, Allison C Morgan, Kivan Polimis, Adaner Usmani, Tong Wang

{"title":"Humans in the Loop: Incorporating Expert and Crowd-Sourced Knowledge for Predictions Using Survey Data.","authors":"Anna Filippova, Connor Gilroy, Ridhi Kashyap, Antje Kirchner, Allison C Morgan, Kivan Polimis, Adaner Usmani, Tong Wang","doi":"10.1177/2378023118820157","DOIUrl":"10.1177/2378023118820157","url":null,"abstract":"Survey data sets are often wider than they are long. This high ratio of variables to observations raises concerns about overfitting during prediction, making informed variable selection important. Recent applications in computer science have sought to incorporate human knowledge into machine-learning methods to address these problems. The authors implement such a \"human-in-the-loop\" approach in the Fragile Families Challenge. The authors use surveys to elicit knowledge from experts and laypeople about the importance of different variables to different outcomes. This strategy offers the option to subset the data before prediction or to incorporate human knowledge as scores in prediction models, or both together. The authors find that human intervention is not obviously helpful. Human-informed subsetting reduces predictive performance, and considered alone, approaches incorporating scores perform marginally worse than approaches that do not. However, incorporating human knowledge may still improve predictive performance, and future research should consider new ways of doing so.","PeriodicalId":36345,"journal":{"name":"Socius","volume":null,"pages":null},"PeriodicalIF":4.5,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/18/af/nihms-1686808.PMC8112737.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38976258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Placing Racial Classification in Context. 将种族分类置于背景中。

IF 4.5

Socius Pub Date : 2019-01-01 Epub Date: 2019-06-25 DOI: 10.1177/2378023119851016

Robert E M Pickett, Aliya Saperstein, Andrew M Penner

引用次数: 6

Predicting Layoff among Fragile Families. 预测脆弱家庭的裁员情况。

IF 4.5

Socius Pub Date : 2019-01-01 Epub Date: 2019-09-10 DOI: 10.1177/2378023118809757

Caitlin E Ahearn, Jennie E Brand

引用次数: 0

Successes and Struggles with Computational Reproducibility: Lessons from the Fragile Families Challenge. 计算再现性的成功与挣扎：脆弱家庭挑战的教训。