Approaches to Topo-biographies of Indigenous Women: Race, Spatial Narratives, and the Examples of Pocahontas and E. Pauline Johnson
Bibliographic record
Abstract
Based on Collective Biographies of Women data, and part of a project on biography and space, this work in progress shares emerging studies of short narratives about Indigenous women in North America, particularly Pocahontas and E. Pauline Johnson (Tekahionwake). Methods include maps, timelines, and a stand-aside XML schema outlining sample texts at paragraph level. We show ways to read interrelated biographies of women in terms of race and nationality (as in collections of Women of Canada), in both spatial data about sets of lives in one book, and in narrative features such as titles, scenes of renaming, and persona description (native costume). In spite of differences, Pocahontas and Tekhionwake are presented as serving English-North American relations in the role of Indian Princess.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.023 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".