Bibliographic record
Abstract
Novelist Fatou Diome, Senegalese migrant to France, in 2019 reached the twenty-fifth year in her adopted country. Silver-anniversary motives encouraged the author to chart the quarter century of progress of this “megaphone of migritude,” as Lila Azam Zanganeh notably called her. Moving from the rich exegeses of the liminal, haunted, frequently abjected, migritude conditions of her fictional—and often autobiographical—heroines, Diome has now arrived inside the Hexagon, where her words harmonize with a sizable chorus of interior-left establishment voices. However, she has not abandoned her powerful interest in the complexities of migritude’s pains and difficult opportunities. On the contrary, in Marianne porte plainte! Identité nationale: Des passerelles, pas des barrières! (Marianne Complains! National Identity: Gangways, Not Barriers!) (2017), Diome takes up the many threads of the migritude tapestry so fully depicted in her novels and reweaves them into a portrait of an ideal new multicultural French identity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".