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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.

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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

    High Causal Evidence Icon

    Strong evidence the effects are caused by the examined intervention.

  • Moderate Causal Evidence

    Moderate Causal Evidence Icon

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

  • Low Causal Evidence

    Low Causal Evidence Icon

    Little evidence that the effects are caused by the examined intervention.

  • Causal Impact Analysis

    Causal Analysis (No Rating) Icon

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

  • Descriptive Analysis

    Descriptive Analysis Icon

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

  • Implementation Analysis

    Implementation Analysis Icon

    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.

    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.

    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.

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

  • Unfavorable

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

    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.

    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.