Individual safety and health outcomes in the construction industry
Bibliographic record
Abstract
Between 2004 and 2006, 911 self-administered questionnaires were collected from 84 nonresidential Ontario construction sites. Each questionnaire contained 105 questions and took approximately 15 min to complete. This paper presents one study from that research project that seeks to understand the relationship among worker demographics, worker safety attitudes, and worker health and safety outcomes (e.g., worker well-being and accidents). The participants had an average age of 38.3 years with 15.1 years experience in the industry. Short job tenure, age, experience, and job position were highly related to safety outcomes. Apprentices experienced more accidents, whereas supervisors reported more work-related psychological symptoms. Among the situational factors, higher work pressure, high interpersonal conflict, and low-quality leadership were most strongly associated with work-related health outcomes and accidents. Regression models were developed with a maximum adjusted coefficient of determination of 0.28. A graphical means of modeling the data was demonstrated in the form of a Bayesian belief network.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".