Recently Added
CLEAR searches the existing literature for research relevant to this topic area's focus. Browse the most recently reviewed research below.
Displaying 301 - 310 of 776
Study Type: Descriptive Analysis
The authors described two programs partnering with California community colleges—the Mathematics, Engineering, Science Achievement Community College Program (MCCP) and the CalWomen Tech Program—that…Study Type: Descriptive Analysis
This article summarized current gender equity issues in career and technical education (CTE) as well as in STEM fields for high school and college students. Using findings from various other…Study Type: Descriptive Analysis
The authors’ main objective was to develop recommendations for recruiting and developing female faculty in STEM disciplines. The authors conducted a series of eight focus groups with science and…Study Type: Descriptive Analysis
This paper was a literature review of research about gender differences in STEM education levels and careers in the United States, including any evidence available for specific cultural, biological…Study Type: Descriptive Analysis
This paper examined whether people with high math and verbal abilities were more likely to work in STEM occupations at the age of 33 compared with people with high math but only moderate verbal…Study Type: Descriptive Analysis
This study addressed two research questions concerning the retention rates of engineers in the United States: whether more women leave the engineering field because of family-related concerns than…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the Structured Training and Employment Transitional Services (STETS) program on employment rates, earnings, and Social Security Disability Income (…Study Type: Descriptive Analysis
The study’s objective was to examine the effects of the Washington Alternative Work Search Experiment on the employment, earnings, and unemployment insurance benefit receipt among those who…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of providing low-income families with private market housing vouchers on employment, earnings, receipt of public assistance, and receipt of education…Study Type: Causal Impact Analysis
The study’s objective was to explore the relationship between employee training investment, promotion strategies, and employee turnover in credit unions in the United States. Using data from a 13-…
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.