Bibliographic record
Abstract
Le large corpus de travail sur la question des femmes après la Révolution islamique en Iran se concentre principalement sur les discours formels et tire des conclusions universelles à partir de la vie d’un seul segment de femmes. Cet article met l’accent sur la diversité des femmes iraniennes et se concentre sur un village agricole pour discuter des expériences des femmes rurales et examiner comment elles transforment leur vie. L’image qui ressort de l’étude de ces femmes est différente de celle qui correspond aux Iraniennes de la classe moyenne urbaine et contraste avec l’image dominante des femmes musulmanes comme retirées, voilées et passives. Les femmes de ce village font face à plusieurs sortes de rapports de domination qui s’appuient sur le capitalisme, le patriarcat, l’idéologie islamique, la génération, le genre et d’autres facteurs. Cependant, les femmes, individuellement et en tant que groupe, tentent d’améliorer leur situation. Cet article affirme qu’on doit rompre avec la tradition qui considère l’islam comme monolithique, les femmes musulmanes comme passives et les Iraniennes comme ne formant qu’une seule catégorie.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.009 |
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".