Trans*Mediation: Exploring Trans Experience Beyond the Mirror of Representation
Bibliographic record
Abstract
Trans media" usually describes the representation of trans people in media.While trans media have garnered many important critiques for their representations, such analyses tend to overlook the problems of representation inherent to trans phenomena themselves:If "trans" describes movement, how can it be represented?And if trans media resist representation, what are trans media, and what else might they do?This thesis investigates these questions through the author's affective encounter with several media objects made by trans creatives, including an artificially intelligent image generator, a short experimental film, and a Twitterbot.Using a theoretical framework of trans embodiment and new materialist media theory, the author argues that the performative processes of mediation embodied by these media-termed trans*mediation-articulate trans experiences beyond the limitations of representation.Trans*mediation creates opportunities to communicate the experience of shifting subjectivity while skirting cisnormativity, offering novel possibilities for trans expression, recognition, pleasure, and community.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".