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Related Studies

Displaying 1 - 10 of 72
828

Brown, J. R., Kapteyn, A., & Mitchell, O. S. (2016). Framing and claiming: How information-framing affects expected social security claiming behavior. Journal of Risk and Insurance, 83(1), 139-162.

  • Topic Area: Behavioral Finance: Retirement

  • Topic Area: Behavioral Insights

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Federal retirement benefits Behavioral interventions

539

Myers, C. (2007). A cure for discrimination? Affirmative action and the case of California’s Proposition 209. Industrial and Labor Relations Review, 60(3), 379-396.

  • Topic Area: Employer Compliance

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Affirmative action

628

Institute for Women’s Policy Research. (2013). Accelerating change for women faculty of color in STEM: Policy, action, and collaboration. Washington, DC: Institute for Women’s Policy Research.

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

Study Type: Descriptive Analysis

Outcome Effectiveness:

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

499

Kurtulus, F. (2012). Affirmative action and the occupational advancement of minorities and women during 1973-2003. Industrial Relations, 52(2), 213-246.

  • Topic Area: Employer Compliance

Study Type: Causal Impact Analysis

Causal Evidence Rating: Moderate Causal Evidence

Outcome Effectiveness:

Affirmative action Executive Order 11246 (E.O. 11246) Civil Rights Act of 1964

436

Colello, A. (2011). Affirmative action bans and minority employment: Washington State’s Initiative 200. Washington, DC: Georgetown University.

  • Topic Area: Employer Compliance

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Affirmative action

428

McIntyre, R., Paulson, R., & Lord, C. (2003). Alleviating women’s mathematics stereotype threat through salience of group achievements. Journal of Experimental Social Psychology, 39, 83-90.

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

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

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

535

Blanchflower, D.G., & Wainwright, J. (2005). An analysis of the impact of affirmative action programs on self-employment in the construction industry. Working paper no. 11793. Cambridge, MA: National Bureau of Economic Research.

  • Topic Area: Employer Compliance

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Affirmative action

685

Mackin, J., Lucas, L., Waller, M., Carey, S., & Finigan, M. (2010). Anne Arundel County juvenile treatment court outcome and cost evaluation. Portland OR: NPC Research.

  • Topic Area: Justice-Involved Youth

  • Topic Area: Opportunities for Youth

Study Type: Causal Impact Analysis

Causal Evidence Rating: Moderate Causal Evidence

Outcome Effectiveness:

Substance abuse recovery Youth programs Other training and education Behavioral Interventions

613

Fosu, A. (2000). Antidiscrimination measures of the 1960s and occupational mobility: Evidence for black American men. Journal of Labor Research, 21(1), 169-180.

  • Topic Area: Employer Compliance

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Civil Rights Act of 1964

708

Markussen, S., Røed, K., & Schreiner, R. C. (2015). Can compulsory dialogues nudge sick-listed workers back to work? (IZA Discussion Paper No. 9090). Bonn, Germany: Institute for the Study of Labor (IZA).

  • Topic Area: Behavioral Insights

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Behavioral Interventions