The Concept of Small-Scale Mining as an Innovation in Human-Nature Connection
Notice bibliographique
Résumé
This dissertation explores how the diffusion of innovation in endogenous small-scale mining (SSM) can support responsible mineral sourcing and contribute to strong sustainability within the mining industry. SSM is practiced but remains understudied in both the Global North and South despite its growing relevance to sustainable development and raw material security. Often conflated with artisanal mining (ASM) in the Global South and overshadowed by large-scale mining (LSM) in the Global North, SSM constitutes a distinct and underexamined analytical category. This research makes four major contributions. First, it develops a Social Earth Science framework that integrates geological and social sciences. Second, it conceptually matures “endogenous SSM,” a form of mining that emerges from within communities, typically via small and medium enterprises (SMEs) using intermediate technologies. Third, it identifies preconditions for sustainable technology diffusion, expanding understandings of mining innovation. Fourth, it redefines nature to include abiotic Earth materials, enabling the study of miner-identified human–nature connections, positioning SSM as an ecosystem service and conceptualizing minerals as commons. These contributions are grounded in strong sustainability, which views the economy as embedded within social and ecological systems. The research is based on a comparative case study approach. The core case study, based in Yukon, Canada, addresses the lack of empirical research on SSM in high-income contexts. A secondary case in Western Region of Ghana allows for comparative analysis and exploration of conceptual boundaries with ASM. It is guided by a Social Earth Science framework and uses mixed methodologies. One focus is technography, an ethnographic approach used to study relationships between communities, technologies and everyday practices. Fieldwork involved 63 semi-structured interviews and participant observation across 23 mine sites and 4 community events. A strengths-based approach was used to highlight the assets of SSM-practicing communities while identifying areas for improvement. In Yukon, SSM evolved from 19th-century Klondike-era hand mining to mid-20th-century dredge mining and then to today’s SME-run placer operations. Some miners practice “slow mining” by deliberately reducing production to sustain livelihoods. A “floating pool of professionals” circulates knowledge and technology across the region. Formalization in Yukon fosters innovation through dynamic regulation, legal recognition, a supported mining collective, an engaged geological survey and community research and development aimed at improved practice. The region’s transition away from mercury was first driven by technology and later reinforced through social norms and regulation. Bottom-up norms proved more durable and effective than top-down mandates. In Ghana, endogenous SSM also exists although the boundaries between ASM and SSM are porous. A skilled and formalizing cohort is emerging. Participant observation and interviews show that miners are not simply ephemeral, low-skilled or poverty-driven. Many are seeking the opportunity to pursue their chosen livelihood within their local communities in a legal and sustainable way over the long term. Two case sites, one mercury-free and one using controlled chemical methods, demonstrate innovation and professionalization among miners. Despite progress, miners face structural and geological barriers. Recognizing this advanced segment challenges dominant narratives and underscores the need for differentiated policy to address varying needs across the ASM–SSM sector. This research shows that innovation diffusion in endogenous SSM can support responsible sourcing aligned with strong sustainability. Sustainable outcomes are possible when local institutions are nested in broader governance systems, the sector is externally recognized, innovation networks are place-based, livelihoods are secure, and governance frameworks prioritize community-scale development. This research positions endogenous SSM as both a conceptual and practical innovation in human–nature connection and as essential for building just, sustainable and secure mineral futures.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,033 |
| Communication savante | 0,005 | 0,007 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».