Unarrested Archives: Case Studies in Twentieth-Century Canadian Women's Authorship
Bibliographic record
Abstract
Calling upon the archives of Canadian writers E. Pauline Johnson (1861-1913), Emily Carr (1871-1945), Sheila Watson (1909-1998), Jane Rule (1931-2007), and M. NourbeSe Philip (1947- ), Linda M. Morra explores the ways in which women's archives have been uniquely conceptualized in scholarly discourses and shaped by socio-political forces. She also provides a framework for understanding the creative interventions these women staged to protect their records. Through these case studies, Morra traces the influence of institutions such as national archives and libraries, and regulatory bodies such as border service agencies on the creation, presentation, and preservation of women's archival collections.The deliberate selection of the five literary case studies allows Morra to examine changing archival practices over time, shifting definitions of nationhood and national literary history, varying treatments of race, gender, and sexual orientation, and the ways in which these forces affected the writers' reputations and their archives. Morra also productively reflects on Jacques Derrida's Archive Fever and postmodern feminist scholarship related to the relationship between writing, authority, and identity to showcase the ways in which female writers in Canada have represented themselves and their careers in the public record
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.059 | 0.024 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".