1IMPACT BENEFIT AGREEMENTS BETWEEN ABORIGINAL COMMUNITIES AND MINING COMPANIES: THEIR USE IN CANADA
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
Solidaria para el Desarrollo. The purpose of this collaboration, which has been supported with funding from the Canadian International Development Agency (CIDA) and the Weedon Foundation, is to build capacity among communities affected by mining in Peru and Canada, based on the belief that, by exchanging information and experiences between these communities, they will be better equipped to defend their rights and interests vis-à-vis mineral development projects. In the past, such projects have proved to have significant adverse environmental, social, cultural and economic effects. The report presents an overview of impact and benefit agreements (IBAs). These agreements are signed between mining companies and First Nation communities in Canada in order to establish formal relationships between them, to reduce the predicted impact of a mine and secure economic benefit for affected communities. IBAs are increasingly used by First Nations in Canada to influence decision making about resource exploitation in their lands. In negotiating and implementing these agreements, communities are learning important lessons that can help others in Peru or elsewhere in Canada. Despite years of experience negotiating these agreements in Canada, the corresponding
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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