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Related Studies

Displaying 651 - 660 of 701
1721

Coile, C., Duggan, M., & Guo, A. (2015). Veterans’ labor force participation: What role does the VA’s disability compensation program play? American Economic Review, 105(5), 131-136.

  • Topic Area: Veterans

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Other wages and benefits Veterans' reemployment

1968
Davis, M., Sheidow, A. J., McCart, M. R., & Perrault, R. T. (2018). Vocational coaches for justice-involved emerging adults. Psychiatric rehabilitation journal, 41(4), 266-276.
  • Topic Area: Low-Income Adults

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

Employment and Training Services Youth programs Training and Education

1445

Farooq, A., & Kugler, A. D. (2015). What factors contributed to changes in employment during and after the great recession? IZA Journal of Labor Policy, 4(3), 1-28.

  • Topic Area: Veterans

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Veterans' reemployment Work Opportunity Tax Credit (WOTC)

462

Denner, J. (2011). What predicts middle school girls’ interest in computing? International Journal of Gender, Science and Technology, 3(1), 54-69.

  • Topic Area: Women in Science, Technology, Engineering, & Math (STEM)

Study Type: Descriptive Analysis

Outcome Effectiveness:

Youth programs Science, Technology, Engineering, and Math (STEM) programs

857

Butler, D., Alson, J., Bloom, D., Deitch, V., Hill, A., Hsueh, J., Jacobs, E., Kim, S., McRoberts, R., & Redcross, C. (2012). What strategies work for the hard-to-employ? Final results of the Hard-to-Employ demonstration and evaluation project and selected sites from the Employment Retention and Advancement project. (OPRE report 2012-08). Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. [Minnesota Tier 2]

  • Topic Area: Low-Income Adults

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Other employment and reemployment Substance abuse recovery

856

Butler, D., Alson, J., Bloom, D., Deitch, V., Hill, A., Hsueh, J., Jacobs, E., Kim, S., McRoberts, R., & Redcross, C. (2012). What strategies work for the hard-to-employ? Final results of the Hard-to-Employ demonstration and evaluation project and selected sites from the Employment Retention and Advancement project. (OPRE Report 2012-08). Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. [NYC PRIDE]

  • Topic Area: Low-Income Adults

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Other employment and reemployment Unemployment Insurance

855

Butler, D., Alson, J., Bloom, D., Deitch, V., Hill, A., Hsueh, J., Jacobs, E., Kim, S., McRoberts, R., & Redcross, C. (2012). What strategies work for the hard-to-employ? Final results of the hard-to-employ demonstration and evaluation project and selected sites from the Employment Retention and Advancement project. (OPRE Report 2012-08.) Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. [NYC SACM]

  • Topic Area: Low-Income Adults

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Other employment and reemployment Substance abuse recovery

1136

Bailey, J. (2014). Who pays the high health costs of older workers? Evidence from prostate cancer screening mandates. Applied Economics, 46(32), 3931-3941. doi:10.1080/00036846.2014.948673

  • Topic Area: Older Workers

Study Type: Causal Impact Analysis

Causal Evidence Rating: Moderate Causal Evidence

Health insurance Older workers' programs

576

Riegle-Crumb, C., Moore, C., & Ramos-Wada, A. (2011). Who wants to have a career in science or math? Exploring adolescents’ future aspirations by gender and race/ethnicity. Science Education, 95(3), 458-476.

  • Topic Area: Women in Science, Technology, Engineering, & Math (STEM)

Study Type: Descriptive Analysis

Outcome Effectiveness:

Youth programs Science, Technology, Engineering, and Math (STEM) programs Other disparities or discrimination in employment and earnings

629

Hill, C., Corbett, C., & St. Rose, A. (2010). Why so few? Women in science, technology, engineering, and mathematics. Washington, D.C.: American Association of University Women.

  • Topic Area: Women in Science, Technology, Engineering, & Math (STEM)

Study Type: Descriptive Analysis

Outcome Effectiveness:

Youth programs Science, Technology, Engineering, and Math (STEM) programs Other disparities or discrimination in employment and earnings