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Record W7133073972

An investigation of attitudes towards safety in the Ontario construction industry

2005· dissertation· W7133073972 on OpenAlexaboutno aff
Dimitrios Karahalios

Bibliographic record

VenueTSpace · 2005
Typedissertation
Language
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Construction industrySafety climateAffect (linguistics)Occupational safety and healthPerceptionWorkplace safetySample (material)
DOInot available

Abstract

fetched live from OpenAlex

Safety climate research is a fundamental organizational approach to safety that entails identifying attitudes and perceptions that may be root causes of workplace incidents and injuries. This study provides a construction industry specific questionnaire that documents worker attitudes and perceptions towards a variety of organizational and physical site factors that affect safety on construction sites. A total of 275 construction workers completed the survey. Thirteen safety attitude factors were found to be consistent over the entire sample of participants. A variety of statistical methods identified numerous relationships between the factors and demographic characteristics of the participants. Most important of those were the four factors found to be statistically significant with safety performance (measured from self reported incident data). In addition to the safety climate research, attitudes towards the main causes of injuries and site safety inspections were documented. Recommendations for future construction safety climate were given.

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)0.002
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 score0.074
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.124
GPT teacher head0.515
Teacher spread0.391 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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