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Record W2056606367 · doi:10.2495/safe-v4-n1-77-86

A new safety culture measurement tool and its application

2014· article· en· W2056606367 on OpenAlexvenueno aff
Lei Wang, Ruishan Sun

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaEuropean Commission
KeywordsReliability engineeringOccupational safety and healthEngineeringComputer scienceMedicine

Abstract

fetched live from OpenAlex

Safety culture has become an important issue in research and industry fi eld due to its latent implications on safety performance. The main aim of this research was to develop a reliable tool to measure organizational safety culture in a quantitative way. First, the dimensions and components of safety culture were analyzed and an integrated safety culture model (ISCM) was developed for describing the two-level structure of safety culture. Second, two forms of safety culture evaluation index system were constructed and every index was described in intrinsic latency and extrinsic indication level. Then the weights of index were determined using the Delphi method and the reliability of the index system was also examined based on data from survey. Third, the fuzzy comprehensive evaluation procedure on safety culture was proposed and the evaluation case was also given. The application case proved the effectiveness and reliability of this measurement tool.

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)0.007
metaresearch head score (Gemma)0.021
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.027
GPT teacher head0.364
Teacher spread0.337 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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