Exploring Profeminist Masculinity Studies through Postmodern Literature: Youth Engagement, Fictional Practice and Feminist Pedagogy
Bibliographic record
Abstract
Antifeminism is one of the persisting tendencies in feminist classes that alienates the majority of adult male students, especially in countries with conflicting models of behavior, like Iran, from the advocacy of women’s rights, and perpetuates misogyny in educational contexts. To overcome (the male) students’ resistance to feminism, the present study uses literary study techniques to create a safe conciliatory space in classrooms for promoting more inclusive and more flexible feminist discussions among students. The research starts with analyzing the impact of literature in activating critical thinking of students, and explains how literature helps learners to question patriarchy from within. To have a more effective literary study in feminist pedagogy, the study focuses on incorporating profeminist masculinity studies and postmodern fiction in curriculum, and it elaborates on how their intersubjective approaches to sexism take students beyond the essentialist gender-war mentality to help them scrutinize gender inequity in relationship with class, race, and sex discriminations. For further practice-based elaborations, the study proposes alternative strategies for reading Julian Barnes’ Arthur & George to show how profeminist studies on a postmodern work of art can motivate students to challenge gender hierarchies, and to accept their own role and responsibility in the development of social justice
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".