Bibliographic record
Abstract
The United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) offers guidance on how the rights of indigenous populations could be protected in the context of member states of the United Nations. While the Declaration prescribes what states need to do to effectively realize its objective, question is whether there are expectations on non-state actors such as corporations to contribute towards attaining those objectives. Though on the one hand the UNDRIP is textually not directed at corporations, on the other hand, corporations are routinely implicated in environments where massive violations of indigenous rights have occurred in various regions of the world. The main argument of this paper is that whereas the UNDRIP does not specifically mention corporations, the contributions of businesses would nonetheless be essential for the effective implementation of UNDRIP in Canada. In the paper, I intend to examine how the text of the indigenous policies of Canadian corporations align with objectives of the UNDRIP. I do so by analyzing a representative sample of indigenous human rights policies of Canadian corporations to see the extent that they engage with the UNDRIP and whether their policies could facilitate best-practice ideas for UNDRIP implementation. The sample policies will be assessed for their substantive content, normative language, potential weaknesses, and possible impact on UNDRIP implementation in the Canadian context. In particular, I will pay close attention to whether the studied policies have enough ingredients to meaningfully contribute to the achievement of UNDRIP goals in Canada as well as indicate any possible impacts they could have on broader corporations/indigenous communities’ relations.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".