Bibliographic record
Abstract
Genealogy, or the study of one's ancestral patri-lineage, has a long and esteemed pedigree in French Canadian and Québécois history. From Cyprien Tanguay's late-nineteenth-century encyclopedias to René Jetté's updated versions more than a century later, genealogy has been an important component of French Canadian nationalisms. Tracing one's ancestry back to the early St. Lawrence settlement in the seventeenth century has provided Québécois subjects with opportune political and social capital with which to make territorial and national claims legitimate. Through a case study approach, I explain how genealogy provides the grounds upon which Québécois and French subjects remember a shared past. Specifically, I examine a variety of sites of memory in the French countryside, including a museum that relies on ‘genealogics’ to call the French Canadian Québécois back to its roots. As such, I demonstrate how the biological, read as a contemporary articulation of Balibar's notion of the racial supplément necessary to nation building, travels across the Atlantic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".