Slips trips and falls in Northern Ontario underground hard-rock mines
Bibliographic record
Abstract
Underground mining environments are dark, wet, and have uneven terrain that can create a risk for slips, trips, and falls (STFs). Ontario hard-rock mine workers are legally required to wear personal protective equipment (PPE). Underground miners also work in a dark and dusty environment with uneven terrain, many work shiftwork, and many work on or around large equipment. There is limited research on STFs in underground mining (Dobson et al., 2015) and to my knowledge workers in underground hard-rock mines have not been surveyed about their perceptions of STF risk factors. This study was conducted to advance understanding of risk factors for STFs in underground mines in Northern Ontario, with an aim to provide recommendations for underground safety guidelines, training procedures and future research. 152 underground workers from 2 mine sites in Northern Ontario completed a survey regarding STF in underground mining. The survey contained 16 open-ended and 6 closed-ended questions that addressed demographics, working roles, and perceptions of STF risk factors pertaining to personal, environmental, work task and PPE related factors. Closed-ended questions were coded and analyzed in SPSS. Open-ended questions were analyzed using the Braun and Clark. (2019) method of thematic analysis The top 10 identified risk factors included uneven terrain, puddles/holes, poor lighting, slippery surfaces, fatigue, getting in/out of equipment, clutter in the walkway, poor vision, walking long distances, and poor balance. Workers identified work environment as the primary component of STF risk, as 5 of the top 10 risk factors indicated are a sub-set of environmental factors. When asked what contributed to the risk of STF 29 of 152 underground workers discussed housekeeping and maintenance of roadways. 54.6% (n=83) of workers strongly agreed that climbing on/off equipment was also a major risk factor for STFs and ranked it 6 out of 10. Workers also identified fatigue as a risk factor as it was ranked 5 out of 10. 54% (n=82) agreed and 30.3% (n=46) strongly agreed that their personal level of fatigue was a risk factor for STFs. Responses indicated that 80.9% (n=123) and 52% (n=79) of workers felt that they were more likely to experience a STF towards the end of their shift and beginning of their shift respectively. Workers also indicated that they aware of the risk factors in their workplace as 59.3% strongly agreed to this statement. Future research on the top 10 identified risk factors (uneven terrain, puddles/holes, poor lighting, slippery surfaces, fatigue, getting in/out of equipment, clutter in the walkway, poor vision, walking long distances, poor balance) would be beneficial to further understand how each factor affects a worker’s risk of experiencing a STF.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".