Bibliographic record
Abstract
The article presents an analysis of emancipation narratives (ENs), or autobiographical stories with a liminal plot which recount the first time the narrators identified with feminist ideas and/or values — an event we will refer to as feminist conversion. The study sample included 152 narratives in English (Internet posts and comments on the topics How did you become interested in feminism?; How did you/I become a feminist? and the collection Becoming feminists: An anthology of how we became feminists. Toronto, 2011). The narratives appeared online in 2009–2013 and were produced by women aged 15–65, all of them residents of the UK, USA and Canada and self-labelled feminists. Our findings suggest that ENs are a valuable source of evidence on the cultural, social and political factors which female narrators consider relevant to feminist conversion, as well as on the mechanisms involved in the narrative reconstruction of causes, consequences and axiological dimensions of conversion. Refs 40.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".