4.11-P14Variations in availability and approach to clitoral surgery for female genital mutilation/cutting in receiving (and source) countries
Bibliographic record
Abstract
Background: Clitoral reconstruction is a surgical intervention which removes the scar tissue resulting from female genital mutilation/cutting (FGM/C), exposes the clitoral stump, and creates a neo-prepuce with vulvar skin. The evidence regarding benefits is limited as shown in two systematic reviews published in 2017. However, in some countries enthusiastic proponents are performing it on demand whilst in other countries clinicians and policy makers are either not offering it or offering it in a highly structured and restricted context. Methods: Review and analysis of the literature on clitoral reconstruction in PubMed and direct contacts, from the 1st description in 2003 to September 2017. Results: We identified four models. In the 1st model reconstruction is on demand and is paid for by social security (France, Germany). In the 2nd model reconstruction is limited to special units, who select and monitor (Belgium, Switzerland, Nordic countries). In the 3rd model clitoral reconstruction is not available and in the 4th model it is available but paid for by the patient (US, Africa). Conclusions: There is a gap in knowledge regarding the possible benefits of clitoral reconstruction. There are disparities of access, surgical and non- surgical care and refunding. A qualitative approach would be desirable to better understand the differences in perception and activity of care-givers; women with FGM/C should be included in these studies. Main messages: Clitoral reconstruction should be carefully monitored. Appropriate instruments are necessary to measure the benefits claimed by the proponents: sexual life, aesthetics, identity, comfort, restoration of “normality”, restitution of a stolen part.
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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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.050 | 0.002 |
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".