Mine safety and Industrial accidents at the Générale des Carrières et des Mines, in Katanga, Democratic Republic of Congo
Bibliographic record
Abstract
This paper focuses on the workplace accidents of Gecamines in a comparative perspective. Copper industry has been the cornerstone of Congolese economy since the colonial era. Katanga province is well known for its reserves of copper and cobalt. Many accidents occurred in mining operations of Gecamines. We collected data of accidents from 1957 to 2008 during the fieldwork at Gecamines. Data of this study included only the accidents that required the miner to be absent from work for at least four calendar days. This study aims to determine factors of the accidents at Gecamines in order to suggest the policy to prevent the occurrence of accidents. The results show that miners at Gecamines were more exposed to the risk of accidents than their colleagues of similar industries in Australia, Canada and the United States of America. The average frequency, severity and number fatalities per year of Gecamines were 48, 3, and 9, respectively. These statistics were higher than those of the aforementioned three countries. Gecamines cared for the injured miners thus increasing the operating cost. These results imply that mine safety and working conditions at Gecamines should be improved to reduce the occurrence of accidents. The reduction of accidents should be achieved by training of miners and instauration of inspectors in charge of safety.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| 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; both teacher heads agree on what is shown here.
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".