Grappling with Cisgender Positionality in Applied Linguistics Research with Trans Participants
Bibliographic record
Abstract
Abstract Cisgender researchers can and must take action against transphobia within our spheres of influence (Knisely, 2023; Zimman, 2021). However, these processes, while necessary, can be fraught and problematic. Trans scholars have challenged the exploitative, cisnormative, and appropriative nature of much academic research by cisgender people on transgender people (Radi, 2019). How can cisgender researchers engage in the necessary work of opposing cissexism in our discipline, and can we do so without perpetuating a cycle of epistemic violence? In this paper, I offer critical reflections as a cisgender researcher on designing a research project on the language learning experiences of non‐binary youth, grounded in scholarship by trans thinkers (Keenan, 2022; Nicolazzo (2017)), and collaborative research methodologies (Jourian & Nicolazzo, 2017; Mayo, 2017). I first discuss my own positionality as a cisgender individual. I then present three insights into what cisgender positionality means and the implications of these for researchers in Applied Linguistics. First, cisgender positionality means having limited personal experience with gender as complex and multidimensional, which requires nuancing how we ask questions related to identity, socialization, language, and embodiment. Second, cisgender positionality means being positioned as epistemic authorities, which necessitates deliberately centering participants as experts and analysts of their experiences. Third, cisgender positionality means benefiting from unearned privilege, which compels us to design research that directly benefits trans individuals and communities. Finally, I propose a critical self‐reflection protocol for cisgender researchers for engaging ethically with trans participants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".