Iranian homosexuals; social identity formation and question of femininity
Bibliographic record
Abstract
Homosexuality and homosexual subjects have been oppressed during the sociocultural transformations of contemporary Iran while femiphobic attitudes have been central to this marginalization. Notwithstanding the profound distortion of the concepts of femininity and masculinity in the course of the modernization and islamization of the country, defeminization of the public space and prioritization of the masculinity in gender discourses have been crucial to all social transitions that intend to feed their desired social-ideal identity. Iranian homosexuals, who are condemned both for their sexuality and nonconformist gender effeminacy, have recently formed fictive kinships and backstage friendship groups in order to negotiate and attain a new social identity. In this paper I will examine the basic reasons behind the rejection of homosexuality in Iran and the ventures of the Iranian gays into cyberspace and back to society, while struggling to construct a new feminine-admissive social identity. The final part of this study is devoted to the discussion of the seat of femininity, particularly effeminacy, among Iranians. The paper concludes with demonstrating the incomplete social identity formation of gays, but also envisages a rising divergence in Iranian youths’ gender behaviors which grants the likelihood of negotiating the newly developed social identity to homosexuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".