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Record W4404120822 · doi:10.24908/qap.v1i2.17346

Female Genital Mutilation in Somalia: Leveraging Opinions, Perceptions, and Experiences for Effective Interventions

2024· article· en· W4404120822 on OpenAlexaff
Jessica Lee

Bibliographic record

VenueQapsule Queen s Undergraduate Health Sciences Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsQueen's University
Fundersnot available
KeywordsFemale circumcisionPsychological interventionPerceptionSex organPsychologyMedicineEnvironmental healthObstetricsNursingBiology

Abstract

fetched live from OpenAlex

This review critically examines the socio-cultural and religious landscape of female genital mutilation (FGM) in Somalia, where the practice remains pervasive despite global condemnation and human rights infringements. With the highest FGM rates globally, Somalia's scenario underscores the complexities of eradicating practices deeply embedded in societal fabric. The purpose of this review is to understand prevailing attitudes towards FGM among various Somali stakeholders and to recalibrate intervention strategies accordingly, with an emphasis on harm reduction as a pragmatic initial approach towards a long-term eradication goal. The review employs a thematic synthesis of qualitative studies to discern Somali communities’ awareness of FGM health risks, ongoing support for the practice, and resistance to its abandonment. It reveals a perceptual shift towards Sunna, a less extreme FGM form, influenced by religious considerations and health awareness, yet still infringing on women's rights. The contentious role of medicalization as a harm-reduction tactic is also discussed, which, while safer, may perpetuate the practice. Overall, the review underscores the necessity for culturally sensitive, community-driven interventions that advocate for collective action against FGM. These interventions should integrate educational efforts, legal frameworks, and redefinition of FGM's socio-cultural importance, aiming for a gradual yet definitive end to the practice.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.404
Teacher spread0.352 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueQapsule Queen s Undergraduate Health Sciences JournalSame topicFemale Genital Mutilation/Cutting IssuesFrench-language works237,207