Bibliographic record
Abstract
Turnor is to tell his story as truthfully and as compellingly as possible.To do so, I have chosen two narrative voices.The primary voice is that of the biographer, narrating Turnor's story based on the historical record-particularly journals, maps, and correspondence.When, on occasion, I have dramatized a scene, it is prompted by Turnor's own dramatic telling of events as found in his journals and duly noted in the endnotes.A secondary narrative line is written in my personal voice.Introduced as jOURNal ONe, jOURNal twO, etc., these sections are set off with a dotted line in the margin, and they begin and end with a decorative ornament.These diary-like journals, placed throughout the book, allowed me the latitude to imagine Turnor's interior life, to speculate, to speak about the biographic process, and to make history personal.Regarding terminology, I want to note that in Philip Turnor's time, the word "Indian" was the common term used to refer to the original peoples of the lands that we now know as Canada.Respecting the more preferred and accurate naming practices of today, I have used this word only when quoting primary material.Where possible I have provided the names of Indigenous individuals.Similarly, the female partner of a fur trader was called by the French and English traders a "country wife" and the ceremony by which she became his "country wife" as marriage à la façon du pays.These women were seldom named in fur trade documents, and my four-times-great-grandmother's name remains unknown to us.I will refer to her as Turnor's Cree wife.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.286 | 0.208 |
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".