Bibliographic record
Abstract
The metaphysics of gender has largely focused on examples of interpersonal, linguistically articulated misrecognition. Cases of linguistic misgendering center an interaction between two people where one person refuses to recognize the gender identity of another. In light of these cases, metaphysicians of gender have devoted substantial attention to defining gender kinds and concepts. In this paper, I consider a different set of examples. I discuss cases of structural, materially articulated violence, patterns of targeted structural violence toward trans and gender-nonconforming people. Specifically, I argue that this kind of structural violence is explained by the gender binary, a social structure that (a) dictates the descriptive expectation that there are two biologically grounded genders, male and female, and (b) divides up social roles based on whether a person is male or female. I claim that metaphysicians of gender need to give a real definition of the gender binary, and I present my own preliminary account. The methodological upshot of this paper is that the metaphysics of gender is not limited to the task of determining who is (or is not) really a member of a gender kind.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.051 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".