Bibliographic record
Abstract
This article focuses on a poignant story told by an elderly Chipewyan or Dené woman—Mrs. Nataway—about the hardest winter of her life. She wished to tell me this story to counter any excessively romantic apperception I might have attained of the traditional caribou‐hunting and fishing life in the northern Canadian transitional forest and barrenlands. In traditional Dené culture, storytelling, or giving gifts of words, is a holy activity that is a part of a broader system of reciprocity whereby knowledge/power cycles and the cosmos is prevented from reverting to chaos. In the manner of all elderly storytellers, Mrs. Nataway was concerned that my account of her words be true, since stories are inspired by the animals and inaccuracy can lead to being “out of luck” or having “bad luck” if they are offended. But a more basic concern is that knowledge cannot be empowering if it is not true. The truth is a central consideration in Chipewyan cosmology, wherein the universe is a moral not a mechanistic system. Mrs. Nataway was concerned with didactic, practical, and moral truth, and with the broader emotional truth that tends to be beyond explication. Her story could only be empowering to the extent that the listener could actually feel what the times of hardship were like when she was young, a time when nearly all of the Dené lived year‐round in the bush.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.018 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".