Queering Methodologies: Challenging Scientific Constraint in the Appreciation of Queer and Trans Subjects
Bibliographic record
Abstract
Qualitative studies require a queer perspective to challenge stagnant forms of scientific discourse. This paper argues for a deconstruction of hegemonic qualitative practices in order to appreciate and listen to queer and trans subjects when employing qualitative research and methodologies. I focus on qualitative methods from an audiovisual perspective to suggest that there is scientific constraint in the way researchers still approach qualitative methodologies. I propose some foundations for thinking about queer qualitative methods that employs queer theory in relation to a self - reflexive creative perspective towards ethics, research and representation. Moreover, I critically analyze the HBO trans documentary, Middle Sexes: Redefining He and She (Antony Thomas 2005), in order to move beyond complacent documentaries that employ interviews as a way of categorizing and containing gender diversity. I work towards future methodological promises for the exploration of queer and trans subjects. Further, this paper challenges the problems of imposing binary - based categories that not only obscure thorough understandings of gender but also perpetuate social injustice.
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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 | 0.356 | 0.268 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.018 | 0.146 |
| Scholarly communication | 0.024 | 0.033 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".