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 in 2019.
Recently Added
Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of Troubled Asset Relief Program (TARP) chief executive officer (CEO) compensation restrictions on the earnings of CEOs. The author…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of immigration policies after September 11, 2001, on self-employment among Mexican immigrants. The study used a difference-in-differences…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of iThrive, a workplace wellness program developed at the University of Illinois at Urbana-Champaign, on employment, productivity, employer…
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.