Work-related mild-moderate traumatic brain injury and the construction industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Consequences of traumatic brain injury underscore the need to study high-risk groups. Few studies have investigated work-related traumatic brain injuries (WrTBIs) in the construction industry. OBJECTIVE: To examine WrTBIs in Ontario for the construction industry compared to other industries. METHODS: A retrospective study of individuals who sustained a WrTBI and had a clinical assessment as an outpatient at a hospital-based referral centre. Data were collected for a number of factors including demographic, injury and occupation and were analyzed according to the Person-Environment-Occupation (PEO) model. PARTICIPANTS: 435 individuals who sustained a WrTBI. RESULTS: There were 19.1% in the construction industry, 80.9% in other industries. Compared to other industries, individuals in the construction industry were more likely to be male, to not have attained post-secondary education, and experience multiple traumas. WrTBIs in the construction industry were commonly due to elevated work. The construction occupations involved included skilled workers and general labourers, and compared to other industries, WrTBIs occurred most often for those employed for a short duration in the construction industry. CONCLUSIONS: Construction industry workers experience serious WrTBIs that are amenable to prevention. Use of the PEO model increased our understanding of WrTBIs in the construction industry.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it