None of the Boys: Transmasculine Representation and Dominant Practices of Masculinity
Bibliographic record
Abstract
Despite the recent proliferation of trans representation in popular culture, transmasculine individuals have not received the same level of representation as transfeminine persons. Through a critical discourse analysis of selected media, this paper aims to highlight the dearth of positive, intersectional transmasculine representation in Western media and culture. The ways in which transmasculine individuals may both benefit from and be subjected by the patriarchal structure of Western society will be explored alongside a critique of how transmasculine persons are constructed by popular media. This paper will explore the ways in which the dominant culture of hegemonic masculinity affects the visibility of transmasculine identities and how they fit within these gendered systems of power. This work seeks to problematize these popular constructions and identify ways in which transmasculinity is systematically delegitimized, allowing for the identification of notable gaps in the provision of social and support services.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Critical discourse analysis of transmasculine representation in popular media; the object is media representation.
The paper studies transmasculine representation in popular media and culture.
Media/gender studies of transmasculine representation, not research practice.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.006 | 0.005 |
| 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".