Escaping social rejection, gaining total capital: the complex psychological experience of female genital mutilation/cutting (FGM/C) among the Izzi in Southeast Nigeria
Bibliographic record
Abstract
BACKGROUND: While the deleterious effects of FGM/C on physical health are well documented, the psychological experience of this harmful practice is a neglected area of research, which limits global mental health actions. As FGM/C was a traditional practice in some areas of Nigeria, the study aimed to understand the psychological experience of FGM/C in context. METHODS: This qualitative study was completed in urban and rural Izzi communities in Southeast Nigeria where FGM/C was widely practiced. In-depth interviews were completed with 38 women of the same ethnicity using the McGill Illness Narrative Interview (MINI) to explore the collective psychological experience of FGM/C before, during and after the procedure. The MINI was successfully adapted to explore the meaning and experience of FGM/C. We completed thematic content analysis and used the concepts of total capital and habitus by Bourdieu to interpret the data. RESULTS: During the period of adolescence, Izzi young women who had not yet undergone FGM/C reported retrospectively being subjected to intense stigma, humiliation and rejection by their cut peers. Alongside the social benefits from FGM/C the ongoing psychological suffering led many to accept or request to be cut, to end their psychological torture. Virtually all women reported symptoms of severe distress before, during and after the procedure. Some expressed the emotion of relief from knowing their psychological torture would end and that they would gain social acceptance and total capital from being cut. Newly cut young women also expressed that they looked forward to harassing and stigmatizing uncut ones, therein engaging in a complex habitus that underscores their severe trauma as well as their newly acquired enhanced social status. CONCLUSION: FGM/C is profoundly embedded in the local culture, prevention strategies need to involve the whole community to develop preventive pathways in a participatory way that empowers girls and women while preventing the deleterious psychological effects of FGM/C and corresponding stigma. Results suggest the need to provide psychological support for girls and women of practicing Izzi communities of Southeast Nigeria.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".