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Record W4414188918 · doi:10.1136/jme-2025-110961

Harms of the current global anti-FGM campaign

2025· article· en· W4414188918 on OpenAlexaff
Fuambai Ahmadu, Dina Bader, Janice Boddy, Natasha Carver, Rosie Duivenbode, Brian D. Earp, Birgitta Essén, Ellen Gruenbaum, Saida Hodžić, Sara Johnsdotter, Saffron Karlsen, Sophia Koukoui, Cynthia Kraus, MaríaCaterina La Barbera, Lori Leonard, Carlos D. Londoño Sulkin, Ruth M. Mestre i Mestre, Sarah O’Neill, Christina Pantazis, Maree Pardy, Juliet Rogers, Nan Seuffert, Arianne Shahvisi, Richard A. Shweder, Lotta Wendel

Bibliographic record

VenueJournal of Medical Ethics · 2025
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsUniversity of ReginaUniversité de MontréalUniversity of Toronto
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdVetenskapsrådet
KeywordsEthnocentrismHuman rightsMulticulturalismUnintended consequencesExpansiveCultural diversityRacismFemale circumcisionProfiling (computer programming)

Abstract

fetched live from OpenAlex

Traditional female genital practices, though long-standing in many cultures, have become the focus of an expansive global campaign against 'female genital mutilation' (FGM). In this article, we critically examine the harms produced by the anti-FGM discourse and policies, despite their grounding in human rights and health advocacy. We argue that a ubiquitous 'standard tale' obscures the diversity of practices, meanings and experiences among those affected. This discourse, driven by a heavily racialised and ethnocentric framework, has led to unintended but serious consequences: the erosion of trust in healthcare settings, the silencing of dissenting or nuanced community voices, racial profiling and disproportionate legal surveillance of migrant families. Moreover, we highlight a troubling double standard that legitimises comparable genital surgeries in Western contexts while condemning similar procedures in others. We call for more balanced and evidence-based journalism, policy and public discourse-ones that account for cultural complexity and avoid the reductive and stigmatising force of the term 'mutilation'. A re-evaluation of advocacy strategies is needed to ensure that they do not reproduce the very injustices they aim to challenge.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.434
Teacher spread0.382 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

Explore more

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