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Record W4409989930 · doi:10.4000/13utq

Revising sex and gender in the TEI Guidelines

2024· article· en· W4409989930 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Text Encoding Initiative · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

With the October 2022 release of the TEI Guidelines, the TEI Technical Council introduced a <gender> element and several revisions to the documentation of related elements and attributes. These revisions respond to calls in the TEI community for a way to encode gender in the context of prosopography (or TEI personography), distinct from linguistic morphological gender. In the process of introducing the new encoding, the Council revised passages of the Names, Dates, People, and Places (ND) chapter to remove prescriptive statements about sex and gender, and to modify the TEI’s guidance on representing individual states and traits. Building on the authors’ presentation to the September 2022 TEI Conference, this article discusses the 2022 efforts as one stage in a series of revisions over the past decade, provides background on the theory guiding their work, explores standoff personography applications of the new elements and attributes to a passage of Virginia Woolf’s Orlando, and discusses an experimental encoding of sex and gender in cast lists from early modern playbooks.

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.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.804
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.150
GPT teacher head0.393
Teacher spread0.243 · 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