Two female Francophone characters, Black and Indigenous: from the loss of voice and identity to the reconstruction of their ancestral roots in Maria Campbell's Halfbreed (1973) and Ken Bugul's Le Baobab fou (1982).
Bibliographic record
Abstract
As part of this dissertation, I propose to offer a comparative study of two works in which the main female characters, who are also the narrators, face an identity crisis that gives rise to a strong desire for self-reconstruction associated with the need to (re)discover their ancestral roots: Le baobab fou (1982) by the Senegalese novelist Ken Bugul, whose real name is Mariétou Mbaye Biléoma, and Halfbreed (1973) by Maria Campbell, an author born in the Canadian Prairies. More specifically, the two writers present the intimate journey of a Black or Indigenous woman who, in the face of social prejudice, turns to her childhood, her primitive sources, and her writing to delve into her origins. This work will begin by examining the loss of voice and self-worth experienced by the two protagonists before focusing on the strategies that each of them uses to free herself from her oppression and rebuild her identity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".