Methodology as Pedagogy: Trans Lives, Social Science, and the Possibilities of Education Research
Bibliographic record
Abstract
Over the past decade, public awareness of transgender people has rapidly increased. Yet people who do not conform to the expectations of their assigned gender often face social prejudice and structural marginalization. Within this context, an increasing number of education researchers have shown interest in taking up questions related to transgender communities. Although there is great potential for education researchers to play a useful role in cultivating trans-competent educational environments, this heightened engagement raises new challenges. How can education researchers design methodologies that avoid reinforcing the structures and epistemologies that have done harm to trans people? This article places that question in historical context through an overview of the relationship between transgender people and social science research over the last century, and the emergence of transgender studies as a response to that history. Then, the article presents a consideration of the role of education research in bridging tensions between the fields of social science and transgender studies.
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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 | 0.081 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.012 | 0.108 |
| Scholarly communication | 0.023 | 0.022 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".