Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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. This collection 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, and 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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it