MétaCan
Menu
Retour à la cohorte
Enregistrement W2761770704 · doi:10.3233/wor-172610

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

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

Notice bibliographique

RevueWork · 2017
Typearticle
Langueen
DomaineEngineering
ThématiqueMining and Resource Management
Établissements canadiensLaurentian UniversityPublic Health OntarioUniversity of TorontoSt. Michael's HospitalOccupational Cancer Research CentreCancer Care Ontario
Organismes subventionnairesCanadian Cancer Society Research InstitutePrevent Cancer Foundation
Mots-clésSAFEROccupational safety and healthEnvironmental healthWitnessWork (physics)Mining industryHazardous wasteDiseaseBusinessMedicineEngineeringPolitical scienceLaw

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,028
Score d'incertitude au seuil0,168

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,060
Tête enseignante GPT0,283
Écart entre enseignants0,223 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations14
Publié2017
Routes d'admission3
Résumé présentoui

Explorer davantage

Même revueWorkMême sujetMining and Resource ManagementTravaux en français237 207