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
Displaying 151 - 160 of 187Study Type: Causal Impact Analysis
The study's objective was to examine the impact of two approaches to subsidized employment for Temporary Assistance for Needy Families (TANF) recipients: Paid Work Experience (PWE) in the nonprofit…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of two approaches to subsidized employment for Temporary Assistance for Needy Families (TANF) recipients: Paid Work Experience (PWE) in the nonprofit…Study Type: Causal Impact Analysis
The study's objective was to examine the impact of two approaches to subsidized employment for Temporary Assistance for Needy Families (TANF) recipients: Paid Work Experience (PWE) in the nonprofit…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the Affordable Care Act (ACA) on the probability of retirement, expected age of retirement, and expected age of claiming Social Security benefits…Study Type: Causal Impact Analysis
The study’s objective was to evaluate the effect of a California paid family leave policy (CA-PFL) on employment of middle-aged female caregivers. The study used a difference-in-differences…Study Type: Causal Impact Analysis
The study’s objective was to measure the impact of the Social Security Administrations’ online iClaim system on changes in Social Security Disability Insurance (SSDI) applications, appeals, awards…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of state minimum wage increases on employment. The authors used a difference-in-difference design to estimate the impacts of minimum wage…Study Type: Causal Impact Analysis
The study's objective was to assess the impact of the Affordable Care Act (ACA) on self-employment among older adults. The authors used a difference-in-difference design to estimate the impacts…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of Penny Per Pound (PPP) on daily hours worked. The author used a statistical model to compare the outcomes of workers at a Florida farm who…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of a dance aerobic exercise intervention on workplace stress, absenteeism, and presenteeism (being present at work when ill or otherwise unfit to…
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.