From Qallunaat to James Bay: An Interview with Mini Aodla Freeman, Keavy Martin, Julie Rak, and Norma Dunning by [WRITERS A-D]
Bibliographic record
Abstract
This interview speaks to Mini Aodla Freeman’s Life Among the Qallunaat, a memoir that interlaces vignettes about her childhood in James Bay, Nunavik with her adult life in Hamilton and Ottawa. The book has been published in two editions to date: the 1978 edition with Hurtig Publishers, which heavily revises the memoir, and the 2015 edition with the University of Manitoba Press, which restores the original manuscript. The interviewers met with Aodla Freeman and the editors, Keavy Martin, Julie Rak and Norma Dunning, on June 9, 2015 at Rak’s home in Treaty 6 territory. We discuss the editorial processes of the original and restored publications, as well as the community protocols and conditions of visibility that go into writing and publishing a book. Aodla Freeman shares new stories about James Bay, reflects on the republication of her memoir, and unveils her plans for future projects.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.051 | 0.021 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.010 |
| 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".