167 Minds in Mines- Assessing the psychological wellbeing of mining industry workers in Ontario Canada
Bibliographic record
Abstract
Abstract The following presentation describes the development of the mental health strategy with the integration of a large-scale survey and the results from the Mining Mental Health project in Ontario, Canada. This 5-year research effort included a large-scale survey of the mental health and wellbeing of mining workers (N= 2,224 participants) using several clinical instruments. The research also integrated qualitative results from individual interviews and focus group meetings. The study represents the first of its kind in the mining industry and results confirmed the need for such research. The prevalence of mental health indicators such as depression, suicidality, PTSD, fatigue, burnout, and substance abuse will be discussed during this presentation as well as their correlates. The predictors of workplace absenteeism and the barriers of a successful return to work will be illustrated. The presentation intends to offer guidance on how to develop a mental health strategy from a systems perspective in the mining industry and involve multiple stakeholders in research of this kind. Finally, it will provide suggestions on potential intervention strategies for mining worker health.
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 | 0.003 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".