Movement Frames and African Women's Explanations for Opposing Female Genital Cutting
Bibliographic record
Abstract
This article addresses how people account for their beliefs and what social factors affect or determine those accounts. Considering the explanations women in five African countries give for their opposition to female genital cutting (FGC), we empirically examine the link between movement adherence and frame resonance. Although international anti-FGC activists employ medical and human rights frames to combat the practice, we find most of the women surveyed do not use these frames to account for their opposition to FGC. Rather, they tend to explain their opposition simply by stating female genital cutting is a ‘bad tradition.’ Based on descriptive statistics and the results of HGLM analyses, we conclude that 1) the importance of frame resonance for movement adherence varies across groups, 2) frame resonance is less important to ‘adherents’ whose supportive attitudes predate mobilization, 3) personal factors, such as being circumcised, exposure to western influence, and independence, increase the likelihood that adherents will link into international activist frames, and 4) the medical frame is more persuasive than the human rights frame for African anti-FGC adherents.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".