Bibliographic record
Abstract
For indigenous communities throughout the globe, mining has been a historical forerunner of colonialism, introducing new, and often disruptive, settlement patterns and economic arrangements. Although indigenous communities may benefit from and adapt to the wage labour and training opportunities provided by new mining operations, they are also often left to navigate the complicated process of remediating the long-term ecological changes associated with industrial mining. In this regard, the mining often inscribes colonialism as a broad set of physical and ecological changes to indigenous lands. Mining and Communities in Northern Canada examines historical and contemporary social, economic, and environmental impacts of mining on Aboriginal communities in northern Canada. Combining oral history research with intensive archival study, this work juxtaposes the perspectives of government and industry with the perspectives of local communities. The oral history and ethnographic material provides an extremely significant record of local Aboriginal perspectives on histories of mining and development in their regions. With contributions by: Patricia Boulter Jean-Sébastien Boutet Emilie Cameron Sarah Gordon Heather Green Jane Hammond Joella Hogan Arn Keeling Tyler Levitan Hereward Longley Scott Midgley Kevin O'Reilly Andrea Procter John Sandlos Alexandra Winton
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.955 | 0.937 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".