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Record W7036327881

A Book Of One's Own: Gender Diversity and Non Binary Identities Represented in Recent Literature

2022· article· en· W7036327881 on OpenAlexaboutno aff

Bibliographic record

VenueActa Académica (Acta Académica) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicFeminist Theory and Gender Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBinary oppositionWishPerformative utteranceQueerFeminismTransgenderPhenomenology (philosophy)Gender identityQueer theory
DOInot available

Abstract

fetched live from OpenAlex

Non binary representations openly discussed in literature are a rather recent phenomenon, which goes hand in hand with the social changes witnessed in these past decades.In this essay, books such as Gender Failure (Coyote, Spoon, 2014), Symptoms of Being Human (Garvin, 2016), None of the Above (Gregorio, 2015), I Wish You All the Best (Deaver, 2019) will be analyzed in order to explore how these examples introduce the reader to different perspectives which escape gender normativity. For this purpose, we will discuss a variety of topics, including pronouns and language representations, visibility of non binary experiences, discrimination and resisting binary norms. Authors related to gender discourse, for example, Judith Butler, Riki Wilchins and Mauro Cabral, will be consulted.BibliographyButler, J. (1988) Performative Acts and Gender Constitution: An Essay in Phenomenology and Feminist Theory. Theatre Journal 40, no. 4.Cabral, M., Benzur, G. (2005) Cuando digo intersex: un diálogo introductorio a la intersexualidad. I. W. Gregorio (2015) None of the Above. California: Balzer + Bray. Spoon, Rae, and Ivan Coyote. (2014) Gender Failure. Vancouver: Arsenal Pulp Press.Wilchins, R. A. (2004) Queer theory, gender theory: an instant primer. Los Angeles: Alyson Books.Garvin, J. (2016) Symptoms of Being Human. California: Balzer + Bray. Mason D. (2019) I Wish You All the Best. North Carolina: Push.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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