Bibliographic record
Abstract
There is nothing peaceful about Samia Shariff’s account. Life has not been easy for this Algerian woman, who was born in France. The third child in a Muslim family whose father is a prosperous and respected businessman, Samia was not welcome in a clan where the birth of a daughter was considered a punishment from Allah! A powerful, at times almost unbearable narrative, Veil of Fear draws us into a world of men who justify most of their actions towards women by means of an abusive interpretation of the Koran and its teaching. Thus, from the time of her birth, Samia lives in fear. In fear of her mother, of her father, of the husband she was forced to marry at the age of 16, of the fundamentalists who constantly threaten her, of the obstetricians who want to put her to sleep, of what might happen to her children, of fleeing towards the unknown, of choosing freedom over assured wealth and, above all, of making her daughters live through the same torments she has experienced. Humiliated, beaten, raped, harassed, she had the intelligence and courage to break out of the infernal circle in which a woman depends on the totalitarian power of a man, from generation to generation. Thus, in November 2001, using false passports for herself and her five children, she crossed the Atlantic Ocean and took refuge in Canada, where she was finally able to start a real life as a mother and woman. In a style that is both simple and effective, Samia recounts her life, her trials and, above all, her victories. For several decades she was the instrument of a completely incredible belief system that granted her no rights whatsoever, not even the right to love or even live in peace. In this respect, she is now the spokeswoman for millions of other women who have stories that are similar and possibly even worse, to tell us. In her own words, Samia says, “I lost everything I had in order to obtain what I never had: peace and love.” Translated from the original French language by Jennifer Makarewicz and Robert Marion.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".