“He/his/she/her/father/mother/son/daughter”: A critical reflection of reproductions of cis-normativity and cis-dominance in preparing qualitative data for analysis
Bibliographic record
Abstract
In this research note, we present a critical moment we had as a research team in our work preparing qualitative data for its analysis in which an unanticipated social justice issue was triggered. The moment was related to determining the best ways to anonymize the information—in particular, how to replace what were perceived as “male” and “female” gendered names, family relationships, and roles with the labels of “she/her/mother/daughter” or “he/his/father/son”. The paper begins with a review of the main “do’s and don’ts” of data preparation, followed by our reflections of the social justice issue. Through our differently positioned reflections, we complicate the task of data preparation by revealing the ways in which cis-dominance is upheld by cis-normativity, cis-genderism, and heteronormativity. We end with recommendations for practices that uphold the values and goals of social justice by resisting cis-dominance and challenging the erasures of peoples with fluid genders and identities.
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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 | 0.202 | 0.202 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.034 | 0.107 |
| Scholarly communication | 0.022 | 0.026 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.008 | 0.026 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".