A Systematic Review of Evaluated Labor Market Initiatives Addressing Precarious Employment: Findings and Public Health Implications
Bibliographic record
Abstract
Precarious employment (PE) is a major determinant of population health and contributor to health and social inequities. The purpose of this article is to synthesize and critically appraise available evidence on labor market initiatives addressing PE identified through a systematic review. Of the 21 initiatives reviewed, grouped into four categories-labor market policies, legislation, and reforms; union strategies; apprenticeships and other youth programs; social protection programs-10 showed consistently positive outcomes and 11 a combination of negative, mixed, or inconclusive outcomes. In addition to reviewing the key findings, we discuss public health implications and recommendations related to PE and the implementation and evaluation of initiatives. Given the wide diversity of initiatives, implementation approaches, evaluation methods, and socioeconomic and historical contexts characterizing the labor markets of the countries studied, we refrain from making recommendations regarding the most effective initiatives to address PE. Instead, we discuss several implications concerning the four types of initiatives to further support those searching for solutions to address PE. We strongly recommend tailoring adopted initiatives to local contexts to match a country's specific PE problems and unique labor market and socioeconomic context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".