Understanding the motivations of small-scale miners in Yukon, Canada through a human-nature connection (HNC) framework and meaningful rural work
Bibliographic record
Abstract
Human–nature connections (HNCs) experienced by a community of miners are explored as drivers of small-scale mining in Yukon, Canada. Through 20 placer mine visits and 32 semi-structured interviews with miners, government, and suppliers, the study finds that a connection to nature—not profit—is the primary motivation. Using a HNC framework, the data reveal that miners perceive their livelihoods as meaningful rural work tied to their engagement with the land and natural environment. These connections go beyond material needs, encompassing experiential, cognitive, emotional, and philosophical realms. Yukon miners' ability to make localized decisions and participate in the full mine life cycle highlights the importance of autonomy and proximity to nature. The concept of mining as an ecosystem service emerges when Earth materials are included within the definition of nature. This study challenges dualistic paradigms that separate humans from nature and Earth material needs, and contributes to broader efforts to embed strong sustainability in the mining sector—an approach that recognizes nature as the non-substitutable foundation of all other forms of capital. It also identifies the fragility of HNCs in contexts where excessive stress on ecosystems, remote decision-making, or livelihood insecurity undermines sustainability. Yukon provides a case study for exploring alternative mining models, such as slow mining, which emphasizes responsible practices and local empowerment. These insights contribute to human–nature debates and point toward more sustainable, place-based mining frameworks grounded in strong sustainability principles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".