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Record W2034903100 · doi:10.1037/1076-8998.10.4.504

Railing for Safety: Job Demands, Job Control, and Safety Citizenship Role Definition.

2005· article· en· W2034903100 on OpenAlexaff
Nick Turner, Nik Chmiel, Melanie Walls

Bibliographic record

VenueJournal of Occupational Health Psychology · 2005
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsJob controlJob attitudeJob designJob rotationJob performancePsychologyPersonnel psychologyConstruct (python library)Job analysisJob characteristic theoryControl (management)CitizenshipContext (archaeology)Job strainSocial psychologyOrganizational citizenship behaviorApplied psychologyJob satisfactionManagementOrganizational commitmentComputer scienceWork (physics)EngineeringPolitical science

Abstract

fetched live from OpenAlex

This study investigated job demands and job control as predictors of safety citizenship role definition, that is, employees' role orientation toward improving workplace safety. Data from a survey of 334 trackside workers were framed in the context of R. A. Karasek's (1979) job demands-control model. High job demands were negatively related to safety citizenship role definition, whereas high job control was positively related to this construct. Safety citizenship role definition of employees with high job control was buffered from the influence of high job demands, unlike that of employees with low job control, for whom high job demands were related to lower levels of the construct. Employees facing both high job demands and low job control were less likely than other employees to view improving safety as part of their role orientation.

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)0.005
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.160
GPT teacher head0.524
Teacher spread0.365 · 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

Citations98
Published2005
Admission routes1
Has abstractyes

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