Iranian women’s sexual reconstruction through the internet: Informal education and empowerment
Bibliographic record
Abstract
The emergence of the internet offered a unique space for Iranian women to inquire about their personal autonomy, including sexual autonomy. While the internet accelerated Iranian women’s emancipation from sexual subordination, critical questions concerning the impact of socio-cultural mores on this relatively new experience remain convoluted. Grounded in critical feminist and sexual script theoretical frameworks, this research investigates some Iranian women’s comprehension and experience of sexual autonomy by closely exploring the educational role of the internet on the discourse of sexual autonomy and its interconnection with the Iranian culture of shame and silence. Through semi-structural in-depth interviews and online ethnography, this research investigates how the internet serves as an informal learning tool that disrupts traditional learning and expedites women’s sexual autonomy in both online and offline spaces. Adopting critical thematic analysis, this study determined that the online realm altered the meaning of sexual subordination and led to a reconstruction that shifted the boundaries of shame and silence around sexuality. Through the interaction and interconnection between online and offline spaces, Iranian women problematize the culture of shame and silence through learning, revisiting their existing knowledge, and then silently acting. Therefore, a cultural reconstruction that is gradually redefining sexual scripts is emerging.
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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 | 0.003 | 0.004 |
| 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 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".