Hunting and the Quest for Power: Relationships between James Bay Crees, the Land and Developers.
Bibliographic record
Abstract
Hunting and "the quest for power" mean different things to different people. "Quest for power" can be a metaphor the James Bay Crees might use for the life of a hunter; it is also a metaphor other Canadians might use for the goals of both northern developers and government bureaucracies. I consider different ideas of hunting, power, and development, and show that how they are used by groups is related to their relationships to the environment and to other peoples. I look first at how James Bay Cree people and hunters often talk and think about themselves and about other beings in their world, and at what kind of relationships they develop. Many Crees, like some other people, approach relationships as the foundations of life. Family relations make it possible to grow from childhood to adulthood, social relations make it possible to become a full autonomous individual by learning how to be a person from and in relations with others. Careful environmental relations make it possible for present generations to work as part of an active world to survive. They also make it possible to exercise some power to shape the world as it is continually emerging by developing potential partnerships with other wilful living beings, including non-humans. Many others approach relationships solely as things which individuals create for their own purposes. For them relationships can be ignored because they think that individuals are separable from their relations to kin, society, and the world. In the later sections of this chapter I focus on how the governments of Canada and Quebec have tried to use or deny relationships in order to control the James Bay Crees and lands, and how the Crees have sought to exercise their autonomy by enhancing recognition of relationships. In doing this I show how environment, economies and politics are intertwined in relationships and conflicts over who governs the James Bay region and how it is to be developed.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.034 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".