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Record W2127829651 · doi:10.1002/ajim.22143

Effectiveness of joint health and safety committees: A realist review

2012· review· en· W2127829651 on OpenAlexafffundabout
Annalee Yassi, Karen Lockhart, Mona Sykes, Brad Buck, Bjorn Stime, Jerry Spiegel

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2012
Typereview
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsGovernment of British ColumbiaUniversity of British Columbia
FundersCanada Research ChairsWorkSafeBC
KeywordsMedicineJoint (building)Occupational safety and healthEnvironmental healthPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Joint health and safety committees (JHSCs) are widely acknowledged as important to a healthy and safe work environment. However, it is also generally believed that having a JHSC is necessary but not sufficient; the JHSC must be effective. METHODS: A systematic review was undertaken to find empirical studies regarding the effectiveness of JHSCs; realist review methodology was applied to determine context-mechanism-outcome patterns. Experts from across Canada and from various sectors and perspectives including government, employers, and unions, were brought together to inform the synthesis. RESULTS: Thirty-one studies met inclusion criteria. Mechanisms identified as important determinants of JHSC effectiveness across various jurisdictions include adequate information, education and training; appropriate committee composition; senior management commitment to JHSCs; and especially a clear mandate with a broad scope and corresponding empowerment (through legislation and/or union presence). CONCLUSIONS: Consistent empowerment mechanisms emerge as determinants of successful JHSCs across contexts despite few evidence-based details for best practice implementation. Intervention research is warranted.

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 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)0.023
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.345
GPT teacher head0.547
Teacher spread0.202 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations78
Published2012
Admission routes3
Has abstractyes

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