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Record W4360613781 · doi:10.1007/s10691-022-09512-7

Roundtable on Deregistration and Gender Law Reform Internationally

2023· article· en· W4360613781 on OpenAlexaff
Jess Smith, Pieter Cannoot, Pierre Cloutier de Repentigny, Lena Holzer, Shelley Leung, Tanya Ní Mhuirthile, Evan Vipond, Nipuna Varman

Bibliographic record

VenueFeminist Legal Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicFeminism, Gender, and Sexuality Studies
Canadian institutionsYork UniversityCarleton University
FundersEconomic and Social Research Council
KeywordsPublic international lawPolitical scienceLawContext (archaeology)SociologyCLARITYJurisdictionLegislationLegislatureConversationInternational lawPublic administration

Abstract

fetched live from OpenAlex

In this roundtable discussion, early-career researchers working in the field of law, gender, and sexuality discuss international and trans-national developments to legal gender. 'The Future of Legal Gender' research project focused on the legislative framework of England and Wales to develop a prototype for decertification. The domestic legislation, however, was situated within a wider international context throughout the project. This roundtable discussion, therefore, provided an opportunity for reflection on the transnational issues raised by decertification, with a particular focus on developments arising in the jurisdiction(s) studied by the early career researchers. The roundtable began with a brief outline of these recent developments before moving to an open discussion on key themes including the value of reform on wider society, changes on-the-ground by non-state actors, and alternative processes for tackling gender inequalities without certifying legal gender. The online conversation took place on 28 June 2021 and has been transcribed and edited for continuity, clarity, and referencing.

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 imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.042
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0120.008
Scholarly communication0.0170.023
Open science0.0040.017
Research integrity0.0190.023
Insufficient payload (model declined to judge)0.0420.005

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 head0.223
GPT teacher head0.431
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2023
Admission routes1
Has abstractyes

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