Living Systematic Annual Search and Review
- The systematic annual search and review (SASR) aims to ensure CLEAR includes the most up-to-date literature on topics of interest to CLEAR audiences, regardless of the size of the evidence base. To accomplish this, the SASR focuses on identifying labor-related research based on the time period it was released.
- The SASR follows a protocol to identify causal studies of a broad range of labor-related interventions—such as employment and training programs, unemployment services, workplace health and safety programs, employment benefits, workers’ compensation, and more— and assesses the quality of the evidence according to CLEAR’s causal evidence guidelines. The SASR considers as all causal studies on labor-related interventions to be eligible for review.
- Once reviewed, profiles summarizing and rating the studies are posted on CLEAR’s Systematic Annual Search webpage, and the relevant topic areas are updated with the latest evidence, as appropriate. All studies included in CLEAR’s database are searchable in the Search for Studies tab.
- CLEAR implements the SASR each year to find the latest research, and also runs other searches by specific time frames of interest, as resources allow.
Status: CLEAR is currently reviewing studies released between 2020 and 2022.
Recently Added
Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the Social Security Annual Earnings Test (AET) on employment.The study used a difference-in-differences design to compare the outcomes of…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of the green initiatives under the American Recovery and Reinvestment Act (green ARRA) on employment.The study used a nonexperimental design. Data were…Study Type: Causal Impact Analysis
The study examined the impact of the American Competitiveness in the 21st Century Act (AC21) which removed H-1B visa quotas for employment in certain industries on foreign-born PhD graduates seeking…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of minimum wage increases on health outcomes.The study used a difference-in-differences design to compare changes in outcomes before and after the…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of reemployment programs on public benefits receipt, employment, and earnings outcomes. This profile focuses on the comparison between the Nevada…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of the Bridge to Employment program on education, employment, earnings, and public benefits receipt.The study used a randomized controlled trial to…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of Ban the Box (BTB) on employment. The study used a nonexperimental design to compare the employment outcomes of individuals in areas that…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of the TRUE Dads program on employment.The study was a randomized controlled trial that assigned co-parenting teams to the treatment or control group.…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of the enhanced Integrated Planning and Advising for Student Success (iPASS) program on education outcomes. This profile focuses on the California…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of the enhanced Integrated Planning and Advising for Student Success (iPASS) on education outcomes. This profile focuses on the Montgomery County…
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.