At the Bridge: James Teit and An Anthropology of Belonging, Wendy Wickwire — A Collective Review
Bibliographic record
Abstract
When one of our co-authors, Rebecca, first encountered Wendy Wickwire's At the Bridge: James Teit and an Anthropology of Belonging, 1 she was immediately struck by the significance of the book's opening passage.She recounts her experience as follows:It is rare, in my first read of a book, that I spend much time with a preface.More frequently, my eyes move quickly over the text, sometimes with a jump, as I feel like a horse at the gate, chomping to run.But there was something in the preface to this book that caught me up short, that left me feeling breathless.It opened with the words of James Teit from a statement he made on behalf of the Allied Indian Tribes of British Columbia to the Senate Standing Committee on Banking and Commerce (Ottawa, 16 June 1920).
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".