Jean-Jacques Chardin, Gwendolyne Cressman et Fanny Moghaddassi (éds), Territory | Territoire(s), Ranam (Recherches anglaises et nord-américaines) n° 57
Bibliographic record
Abstract
This bilingual volume examines the notion of "territory" from different vantage points, bringing together a variety of contributions from diverse fields, with a majority of articles focusing on contemporary literary material from North America. In that sense, Territory/Territoire(s) reflects current efforts in academia to transcend disciplinary boundaries and holds true to the promise of pluri-disciplinarity formulated in the preface. The contributors to this volume have set out to draw the conceptual boundaries of "territory" and explore the multiple ways in which this notion may inform our understanding of certain literary productions, historical events, and sociogeographical realities, from the 16 th century to the present day. They grapple with the semantic multivalence of the term, measure its representational weight, and dissect its political implications across parts of the anglophone world.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".