Towards an Indigenous-Informed Relational Approach to Free, Prior, and Informed Consent (FPIC)
Bibliographic record
Abstract
International and domestic rights frameworks are setting the stage for the full recognition of Indigenous Peoples’ rights in Canada. However, current political promises to restore Indigenous relations, to reconcile historic wrongs, and to foster mutual prosperity and well-being for all people within Canada remain woefully unfulfilled. Indigenous Peoples continue to call for full engagement with emerging Indigenous rights frameworks such as the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) and its principles of free, prior, and informed consent (FPIC). This article discusses the key findings from a multi-year university–community research partnership with Matawa First Nations in which we collaboratively seek to advance understanding of consultation processes and Indigenous experiences of and perspectives on FPIC. The article, based on several years of dialogue and interviews and a two-day workshop on FPIC, offers insight into Indigenous perspectives on FPIC advancing an Indigenous-informed relational approach to consultation and consent seeking.
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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 | 0.305 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.027 | 0.101 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.005 | 0.029 |
| Research integrity | 0.011 | 0.027 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".