Bibliographic record
Abstract
This chapter highlights some of the ways in which a biographical approach can illuminate new pathways for historians, but also its limits. McDonnell started his last project by focusing on what some call a métis “cultural broker.” Imperial officials privileged such men (and more rarely, women) in their orders and correspondence because they were often so dependent on them—as interpreters, mediators, and go-betweens. They were among the few who had access to Indian communities and knowledge about the politics of a world beyond the ken of Europeans. For incoming post commanders, lost missionaries, intrepid new traders in the region—and subsequent historians—men and women who had connections in Indian country were an invaluable resource and helped build a “middle ground” between natives and newcomers. Yet McDonnell eventually realised that these go-betweens often played only a secondary, supporting role. A tentative “middle ground” might have been established between Europeans and Indians at colonial outposts, and that middle ground sometimes acted as a bridge between two cultures, or even among many diverse peoples. But for Indians, European posts were only one among many sites of meeting, encounter, and community.
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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 | 0.001 | 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 | 0.007 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| 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".