MétaCan
Menu
Back to cohort
Record W2164523122 · doi:10.1037/0021-9010.90.1.77

High-Performance Work Systems and Occupational Safety.

2005· article· en· W2164523122 on OpenAlexaff
Anthea Zacharatos, Julian Barling, Roderick D. Iverson

Bibliographic record

VenueJournal of Applied Psychology · 2005
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsLISRELOrganizational safetyOccupational safety and healthEffective safety trainingWork systemsWorkplace safetyWork (physics)Safety behaviorsWork safetySafety cultureSafety management systemsPsychologyStructural equation modelingApplied psychologyOperations managementBusinessHuman factors and ergonomicsManagement systemPoison controlOrganizational commitmentRisk analysis (engineering)EngineeringManagementSocial psychologyComputer scienceOrganizational behavior and human resourcesEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

Two studies were conducted investigating the relationship between high-performance work systems (HPWS) and occupational safety. In Study 1, data were obtained from company human resource and safety directors across 138 organizations. LISREL VIII results showed that an HPWS was positively related to occupational safety at the organizational level. Study 2 used data from 189 front-line employees in 2 organizations. Trust in management and perceived safety climate were found to mediate the relationship between an HPWS and safety performance measured in terms of personal-safety orientation (i.e., safety knowledge, safety motivation, safety compliance, and safety initiative) and safety incidents (i.e., injuries requiring first aid and near misses). These 2 studies provide confirmation of the important role organizational factors play in ensuring worker safety.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.069
GPT teacher head0.466
Teacher spread0.397 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations877
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied PsychologySame topicOccupational Health and Safety ResearchFrench-language works237,207