Unearthing the discursive politics of mining on Indigenous lands: knowledge, health, contestation, and power in contemporary Canadian regulatory infrastructures
Notice bibliographique
Résumé
Mining projects have the potential to significantly affect Indigenous Peoples and their health in myriad ways, both in the short term and across generations. During the approval stage for new extractive sites, a projects’ anticipated impacts on Indigenous Peoples’ health and wellbeing are evaluated using a process called environmental assessment (EA). However, EA is a technocratic process that relies on and advances a very specific and narrow understanding of health— one based in Western colonial cultural understandings and assumptions that can be inappropriate and even harmful for Indigenous communities.This thesis sought to answer two key research questions: how can extractive projects affect Indigenous Peoples’ health, and how is Indigenous Peoples’ health represented in environmental assessment? My methods to answer these questions included a scoping review of the literature on extraction and Indigenous Peoples’ health, as well as a qualitative document analysis of the final environmental assessment reports for 28 mining projects in Canada. I then interpreted the results of these analyses using critical framing techniques borrowed from infrastructure studies to unpack the broader political implications of EA and the kind of knowledge it contains and perpetuates. In the scoping review, I identified a set of mechanisms with the capacity to be activated in an extraction context and produce health outcomes, including: engagement in assessment and consultation processes; interaction with government and industry officials; the presence and nature of new work and training opportunities; changes to the economy and an influx of new money; changing social structures and new inequalities; environmental degradation and dispossession; new and longstanding changes to the economy; and lasting effects on land. The variation in these mechanisms across space and time confirms that communities can be affected by resource projects via a wide range of pathways, which proves that a holistic perspective is necessary to adequately measure and understand effects on Indigenous Peoples’ health. However, the analysis of the EA reports showed that these varied pathways to health were often not included in the assessment process. And, when indicators related to Indigenous health were included, these methods of assessment were at odds with community health ontologies due to their narrow focus and their inability to consider the complexity and essentiality of human-non-human relations. The primary conclusion of this thesis is that EA is largely ineffective at fully or accurately assessing effects of extractive projects on Indigenous Peoples’ health. Beyond identifying a diverse set of fundamental issues with EA’s measurements, I also argue that the process itself leads to a furthering of colonial logics in the public sphere, which is harmful to communities and contributes to asymmetrical power dynamics between Indigenous Peoples and the Crown
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 | 0,017 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,007 | 0,010 |
| Études des sciences et des technologies | 0,027 | 0,049 |
| Communication savante | 0,016 | 0,005 |
| Science ouverte | 0,003 | 0,008 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
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 ».