Notice bibliographique
Résumé
The mining industry provides valuable mined commodities and financial support for communities worldwide. Mining has become safer for workers. Significant injustices, however, are created by mining companies for workers, local communities and the environment. Mining workers are amongst the world’s most vulnerable because of the dangerous nature of their work, inherent health risks, and problematic, neo-colonial ways in which the industry is governed. Given the scope of these problems, solutions are often challenging, yet this article proposes various responses to global mining inequities. In this article, examples of safe and adequately compensated programs to improve workers’ rights, environmental impacts, and social conditions related to mining will be discussed. Here, solutions to some problems caused by mining are examined, with a focus on workers’ health and human rights through unions and cooperatives, targeted programs for improving mental well-being, the feminization of the mining workforce; the possibility of reducing demand for mining products through reuse and reducing consumption. Ameriolating mining governance is key, through enhanced implementation of human rights, safety, and labor standards, specifically applying the Universal Declaration of Human Rights (UDHR) to mining issues; mining justice organizations play a vital role, particularly in accountability and publicity of mining issues. Canada is spotlighted here as it houses approximately 75% of mining company headquarters, primarily due to favorable tax and investment conditions and the concentration of skilled labor. Greater unionization and cooperativization of mining workers hold great promise for improving health and safety conditions of miners. Feminizing the mining workforce promises to improve both productivity and profits. While mental health is often ignored, Australia’s Mates in Mining program has improved mental well-being and reduced depression and suicide amongst mining workers. Expansion of such programs worldwide would positively impact workers, their families, and improve productivity. Moreover, third-party certification for mining workers’ rights, such as Fairmined, ought to be expanded while universal human rights declarations ought to be upheld. Social justice movements improve worker’s rights, environmental impact and social conditions related to mining. In this article, the importance of improving larger socioeconomic and political conditions in which mining workers operate are also examined, such as reducing demand for mined commodities and recycling more effectively. Improving Indigenous land-based rights is another crucial aspect of creating more just mining practices. Mining offers many workers, particularly those in Canada and other high-income nations, a decent income and benefits. Equivalent wages and benefits ought to be paid to all mining workers worldwide. “It is possible to move from tunnel vision-profit-oriented mining practices which damage workers, communities and environment, to light at the end of the tunnel-- healthy workers, communities and environment”.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,012 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,000 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».