Bibliographic record
Abstract
Autofiction: A Female Francophone Aesthetic of Exile e xplores the multiple aspects of exile, displacement, mobility, and identity as expressed in contemporary autofictional work written in French by women writers from across the francophone world. Drawing on postcolonial theory, gender theory, and autobiographical theory, the book analyses narratives of exile by six authors who are shaped by their multiple locales of attachment: Kim Lefèvre (Vietnam/France), Gisèle Pineau (Guadeloupe/mainland France), Nina Bouraoui (Algeria/France), Michèle Rakotoson (Madagascar/France), Véronique Tadjo (Côte d’Ivoire/France), and Abla Farhoud (Lebanon/Quebec). In this way, the book argues that the French colonial past continues to mould female articulations of mobility and identity in the postcolonial present. Responding to gaps in the critical discourse of exile, namely gender, this book brings genre in both its forms — gender and literary genre — to bear on narratives of exile, arguing that the reconceptualization of categories of mobility occurs specifically in women’s autofictional writing. The six authors complicate discussions of exile as they are highly mobile, hybrid subjects. This rootless existence, however, often renders them alienated and ‘out of place’. While ensuring not to trivialize the very real difficulties faced by those whose exile is not a matter of choice, the book argues that the six authors experience their hybridity as both a literal and a metaphorical exile, a source of both creativity and trauma. The autofictional mode of writing becomes a means for the authors to resolve the multiple personal conflicts which arise from their migration.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.404 | 0.116 |
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".