A Story of Marguerite: A Tale about Panis, Case Comment, and Social History
Bibliographic record
Abstract
Those interested in social history contend that social norms deserve attention due to how they impact and are affected by historical events. This subfield has contributed significantly to how larger historical mosaics are understood, and how themes specific to marginalized groups are appreciated today. By presenting the story of enslaved Indigenous woman in New France who was the first Indigenous civil litigant in Canadian history, and focusing on her representation in the colonial legal system, a number of themes emerge. Canada’s history of slavery becomes better understood, and in so doing, a challenge to social historians is presented. By examining the legal procedure applied to an Indigenous litigant’s circumstances, and then dissecting the events that followed, the strength of social norms during her time is appreciated more fully. Integrating an era’s legal doctrine into historical analysis augments the social historian’s search for society influence on the individual in history.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.037 | 0.026 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.009 |
| 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".