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Record W4318066208 · doi:10.1017/jlr.2022.57

The Limits of Defining Identity in Religion-Gender Conflicts: A Response to Patrick Parkinson

2023· article· en· W4318066208 on OpenAlexaff
Laura Portuondo, Claudia E. Haupt

Bibliographic record

VenueJournal of Law and Religion · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsScience North
FundersYale University
KeywordsIdentity (music)SincerityFaithTransgenderGovernment (linguistics)Gender identityBelief systemSocial psychologyPolitical scienceSociologyPsychologyLawGender studiesEpistemologyPhilosophyAesthetics

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.353
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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