“All These Stories about Women”: “Many Tender Ties” and a New Fur Trade History
Bibliographic record
Abstract
about Women": "Many Tender Ties" and a New Fur Trade History Jennifer S.H. Brown on 29 may 2007, i was privileged to be the commentator for a Canadian Historical Association (CHA) Forum in honour of Sylvia Van Kirk, at the annual CHA meeting in Saskatoon.The occasion led me to look back over Sylvia's and my considerable correspondence over the years and to reflect on our work, our mutual interests, and our long friendship.I am happy to have the opportunity to express these thoughts more fully for this book.Sylvia and I have known each other since 1972.Our association over almost four decades has encompassed a period in which women's and Aboriginal history have secured a permanent place in Canadian history.Much has changed in those years-when we began to walk the historical trails we had chosen, they were narrow and we did not have much company.Now they are broad and welltrodden by scholars of many backgrounds who are shedding light on subjects and areas scarcely thought of in the 1970s, as exemplified by several of the studies in this volume.This essay makes no attempt to review the history of these fields over the last decades.I shall try, however, to tell a small piece of their story through some of Sylvia's and my own experiences, beginning with our mutual starting point in the early 1970s.Our scholarly correspondence, begun in 1972, fuelled a friendship as we discovered and shared our research and our common interests and enthusiasms.In following years, our studies were intertwined in continuing
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".