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Record W2761770704 · doi:10.3233/wor-172610

From awareness to action: Sudbury, mining and occupational disease in a time of change

2017· article· en· W2761770704 on OpenAlexafffundabout
Desré M. Kramer, D. Linn Holness, Emily Haynes, Keith McMillan, Colin Berriault, Sheila Kalengé, Nancy Lightfoot

Bibliographic record

VenueWork · 2017
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsLaurentian UniversityPublic Health OntarioUniversity of TorontoSt. Michael's HospitalOccupational Cancer Research CentreCancer Care Ontario
FundersCanadian Cancer Society Research InstitutePrevent Cancer Foundation
KeywordsSAFEROccupational safety and healthEnvironmental healthWitnessWork (physics)Mining industryHazardous wasteDiseaseBusinessMedicineEngineeringPolitical scienceLaw

Abstract

fetched live from OpenAlex

BACKGROUND: Miners work in highly hazardous environments, but surprisingly, there are more fatalities from occupational diseases, including cancers, than from fatalities from injuries. Over the last few decades, the mining environment has become safer with fewer injuries and less exposure to the toxins that lead to occupational disease. There have been improvements in working conditions, and a reduction in the number of workers exposed, together with an overall improvement in the health of miners. OBJECTIVES: This study attempted to gain a deeper understanding of the impetus for change to reduce occupational exposures or toxins at the industry level. It focuses on one mining community in Sudbury, Ontario, with a high cancer rate, and its reduction in occupational exposures. It explored the level of awareness of occupational exposures from the perspective of industry and worker representatives in some of the deepest mines in the world. Although awareness may be necessary, it is often not a sufficient impetus for change, and it is this gap between awareness and change that this study explored. It examined the awareness of occupational disease as an impetus to reducing toxic exposures in the mining sector, and explores other forces of change at the industrial and global levels that have led to an impact on occupational exposures in mining. METHODS: From 2014 and 2016, 60 interviews were conducted with individuals who were part of, or witness to the changes in mining in Sudbury. From these, 12 labour and 10 industry interviews and four focus groups were chosen for further analysis to gain a deeper understanding of industry and labour's views on the changes in mining and the impact on miners' health from occupational exposures. The results from this subsection of the data is the focus for this paper. RESULTS: The themes that emerged told a story about Sudbury. There is awareness of occupational exposures, but this awareness is dwarfed in comparison to the attention that is given to the tragic fatal injuries from injuries and accidents. The mines are now owned by foreign multinationals with a change from an engaged, albeit paternalistic sense of responsibility for the health of the miners, to a less responsive or sympathetic workplace culture. Modernization has led to the elimination, substitution, or reduction of some of the worst toxins, and hence present-day miners are less exposed to hazards that lead to occupational disease than they were in the past. However, modernization and the drop in the price of nickel has also led to a precipitous reduction in the number of unionized miners, a decline in union power, a decline in the monitoring of present-day exposures, and an increase in non-unionized contract workers. The impact has been that miners have lost their solidarity and power to investigate, monitor or object to present-day exposures. CONCLUSIONS: Although an increase in the awareness of occupational hazards has made a contribution to the reduction in occupational exposures, the improvement in health of miners may be considered more as a "collateral benefit" of the changes in the mining sector. Multiple forces at the industrial and global level have differentially led to an improvement in the working and living environment. However, with the loss of union power, the miners have lost their major advocate for miner 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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.060
GPT teacher head0.283
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2017
Admission routes3
Has abstractyes

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