Employment-Low-No impacts

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Displaying 1 - 10 of 107

Inequality and opportunity in work-based learning (Reilly, 2014)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of work-based learning (WBL) on employment and earnings.The study used a nonexperimental design to compare the outcomes of college graduates who…
The effects of need-based financial aid on employment and earnings: Experimental evidence from the Fund for Wisconsin Scholars [Two-Year College Student Sample] (Carlson et al., 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of the Fund for Wisconsin Scholars (FFWS) on employment and earnings. This profile focuses on the outcomes for students enrolled in two-year colleges.…
Medicaid work requirements in Arkansas: Two-year impacts on coverage, employment, and affordability of care (Sommers, 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of work requirements for Medicaid recipients on public benefits receipt, employer benefits receipt, and employment. The study used a difference-in…
Longitudinal outcomes of Project SEARCH in upstate New York (Christensen et al., 2015)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of Project SEARCH on employment and wage outcomes. The authors used an interrupted time series to examine the outcomes of emerging adults with…
The impact of veteran support programs on stress, satisfaction, and retention for veteran employees (Singh, 2019)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of employer-offered veteran transition support programs on veteran job satisfaction levels, stress rates, and retention. This study was a non-…
New insights into the back on track model's effects on opportunity youth outcomes: Opportunity works final evaluation report (Anderson et al., 2019)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of the Back on Track framework on obtaining a high school credential and being disconnected from both work and school (that is, neither working nor…
Effectiveness of screened, demand-driven job training programs for disadvantaged workers: An evaluation of the New Orleans career pathway training (Baird et al., 2019)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of the New Orleans Office of Workforce Development (OWD) Career Pathways training program on employment, earnings, and job satisfaction. This…
Compensatory cognitive training for people with severe mental illnesses in supported employment: A randomized controlled trial (Twamley et al., 2019)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of Compensatory Cognitive Training (CCT) on attaining competitive employment, weeks worked, wages earned, mental illness symptom severity, and…
Integrating service into YouthBuild AmeriCorps HSE and diploma granting programs (The Center for Youth and Communities, 2019)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of YouthBuild AmeriCorps programs that grant both a HSE and Diploma (Combined HSE/Diploma) on employment, and education and training. The authors…
Integrating service into YouthBuild AmeriCorps HSE and diploma granting programs (The Center for Youth and Communities, 2019)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of YouthBuild AmeriCorps programs that grant a high school equivalency credential (HSE-only) on employment, and education and training. The authors…

CLEAR Icon Key

Below is a key for icons used to indicate important details about a study, such as its type, evidence rating, and outcome findings.

High Causal Evidence

Strong evidence the effects are caused by the examined intervention.
Moderate Causal Evidence

Evidence that the effects are caused to some degree by the examined intervention.
Low Causal Evidence

Little evidence that the effects are caused by the examined intervention.
Causal Impact Analysis

Uses quantitative methods to assess the effectiveness of a program, policy, or intervention.
Descriptive Analysis

Describes a program, policy, or intervention using qualitative or quantitative methods.
Implementation Analysis

Examines the implementation of a program, policy, or intervention.
Favorable

The study found at least one favorable impact in the outcome domain, and no unfavorable impacts.
Mixed

The study found some favorable and some unfavorable impacts in the outcome domain.
None

The study found no statistically significant impacts in the outcome domain.
Unfavorable

The study found at least one unfavorable impact in the outcome domain, and no favorable impacts.
Not applicable

Not applicable because no outcomes were examined in the outcome domain.
Favorable - low evidence

The study found at least one favorable impact in the outcome domain, and no unfavorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Mixed - low evidence

The study found some favorable and some unfavorable impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
None - low evidence

The study found no statistically significant impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Unfavorable - low evidence

The study found at least one unfavorable impact in the outcome domain, and no favorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.