Talking with Iranian trans men: Their experiences and identity development
Bibliographic record
Abstract
Introduction This research sought to discover the psychosocial experiences of trans men born and raised in Iran, including the cultural surround unique to Iran.Method Fifteen trans men aged from 20 to 35 narrated their lives through in-depth individual interviews. We applied Corbin and Straus’s (2015) approach to analyze the data in developing a Grounded Theory.Results Confusing Gender Identity (Core Theme) and eleven other themes, divided into (Macro/Micro) Contextual factors, Actions/Interactions, and Consequences, depicting the structures and processes in trans men’s lives. Escalations of Dysphoria within family structure and Traumatic Backgrounds represent Micro-contextual factors; Masculine Superiority and Feminine Gender Taboo are Macro-contextual factors; Insecurity in Emotional Relationships, Social Insecurity, Feminine Inferiority, Masculine Gender Envy, Discordant Self-image, and Unsupportive Systems are the Actions/Interactions, and Gray Fortunes represent Consequences. A Grounded Theory is developed from these findings that comprehensively represent the relational themes.Conclusion The findings clarify the contextual factors affecting Iranian trans men’s lives. They could be applied to improve the overall health of this population. As most studies and theories regarding the transgender population emanate from Western cultures, this research provides a new and comprehensive understanding of trans men’s psychological/social experiences in a unique cultural and political climate.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".