The Limits of Defining Identity in Religion-Gender Conflicts: A Response to Patrick Parkinson
Bibliographic record
Abstract
Abstract In his article “Gender Identity Discrimination and Freedom of Religion,” Patrick Parkinson raises the important question of how the government should reconcile conflicts between the rights of religious people and the rights of transgender and gender-nonconforming people. By focusing on whether gender identity is best defined as a medical issue or a belief system, however, Parkinson does little to answer it. Whether gender identity is a medical issue may be relevant to determining the sincerity of an individual’s faith-based objection to complying with an antidiscrimination law. It has no bearing, however, on the strength of trans and gender-nonconforming individuals’ countervailing interest in being protected from discrimination. Defining gender identity as a belief system does no more to undermine this interest. This should be apparent to defenders of religious exemptions, who assert that belief systems offer a basis for extending, rather than contracting, legal protections. Characterizing an individual’s gender identity as either a medical issue or a belief system thus does not show why that individual’s interests should give way to the interests of religious objectors through an exemption. To reach this conclusion, one must instead turn to other values, such as those implicit—though inadequately defended—in Parkinson’s article.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.033 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.063 |
| Scholarly communication | 0.014 | 0.023 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.043 | 0.068 |
| 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".