Cree agency and environment: rethinking human development in the Cree Nation of Wemindji
Bibliographic record
Abstract
As indigenous peoples strive to navigate development in a way that enhances their agency, advocates of human development and the capabilities approach have increasingly sought to support this objective.To this end, the work of Amartya Sen, a chief advocate of human development, has been influential.While Sen's contribution to development economics through the capabilities approach cannot be underestimated, his understandings of agency in development have been criticized as too limited, failing to significantly integrate group agency and the environment.This thesis examines understandings of agency in the East James Bay Cree community of Wemindji, and compares and contrasts these with that of Amarta Sen, in seeking to reveal where these two perspectives both align and fail to align.Wemindji Cree approaches to development generally, and a prospective gold mine in particular, reveals a perception of agency that challenges the aforementioned limitations of Sen's work.These challenges demonstrate a need to reconsider and expand considerations of agency in human development approaches if these are to help understand and realize Wemindji Cree agency.Over the course of this research, many colleagues, teachers and friends have offered valuable support and insight.I would like to thank my supervisor Dr. Peter G. Brown for his patience, vision and guidance, and also for giving me the opportunity to participate in the Paakumshumwaau-Wemindji protected area project.I am
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.031 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".