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Record W3177015528 · doi:10.1186/s13643-021-01728-z

Initiatives addressing precarious employment and its effects on workers’ health and well-being: a protocol for a systematic review

2021· review· en· W3177015528 on OpenAlexafffund
Virginia Gunn, Carin Håkansta, Emilia Vignola, Nuria Matilla‐Santander, Bertina Kreshpaj, David H. Wegman, Christer Hogstedt, Emily Q. Ahonen, Carles Muntaner, Sherry Baron, Theo Bodin

Bibliographic record

VenueSystematic Reviews · 2021
Typereview
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdVetenskapsrådetKarolinska InstitutetKarlstads universitetMcMaster University
KeywordsMedicineProtocol (science)Systematic reviewMEDLINEAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Precarious employment is a significant determinant of population health and health inequities and has complex public health consequences both for a given nation and internationally. Precarious employment is conceptualized as a multi-dimensional construct including but not limited to employment insecurity, income inadequacy, and lack of rights and protection in the employment relation, which could affect both informal and formal workers. The purpose of this review is to identify, appraise, and synthesize existing research on the effectiveness of initiatives aiming to or having the potential to eliminate, reduce, or mitigate workers' exposure to precarious employment conditions and its effects on the health and well-being of workers and their families. METHODS: The electronic databases searched (from January 2000 onwards) are Scopus, Web of Science Core Collection, and PubMed, along with three institutional databases as sources of grey literature. We will include any study (e.g. quantitative, qualitative, or mixed-methods design) evaluating the effects of initiatives that aim to or have the potential to address workers' exposure to precarious employment or its effects on the health and well-being of workers and their families, whether or not such initiatives were designed specifically to address precarious employment. The primary outcomes will be changes in (i) the prevalence of precarious employment and workers' exposure to precarious employment and (ii) the health and well-being of precariously employed workers and their families. No secondary outcomes will be included. Given the large body of evidence screened, the initial screening of each study will be done by one reviewer, after implementing several strategies to ensure decision-making consistency across reviewers. The screening of full-text articles, data extraction, and critical appraisal will be done independently by two reviewers. Potential conflicts will be resolved through discussion. Established checklists will be used to assess a study's methodological quality or bias. A narrative synthesis will be employed to describe and summarize the included studies' characteristics and findings and to explore relationships both within and between the included studies. DISCUSSION: We expect that this review's findings will provide stakeholders interested in tackling precarious employment and its harmful health effects with evidence on effectiveness of solutions that have been implemented to inform considerations for adaptation of these to their unique contexts. In addition, the review will increase our understanding of existing research gaps and enable us to make recommendations to address them. Our work aligns with the sustainable development agenda to protect workers, promote decent work and economic growth, eliminate poverty, and reduce inequalities. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020187544 .

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Science and technology studies
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.316
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0220.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.247
GPT teacher head0.538
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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".

Quick stats

Citations28
Published2021
Admission routes2
Has abstractyes

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