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Record W4377968854 · doi:10.1093/jsxmed/qdad061.088

(092) What is Sexuality?: Moving Toward Inclusive and Comprehensive Measurement

2023· article· en· W4377968854 on OpenAlexaff
Mark Henkelman, Jeremy Friedman, Meghan K. McInnis

Bibliographic record

VenueThe Journal of Sexual Medicine · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsQueen's University
Fundersnot available
KeywordsHuman sexualityTransgenderPsychologyConstruct (python library)PsychosocialSocial psychologyPleasureDevelopmental psychologyGender studiesSociologyComputer sciencePsychotherapist

Abstract

fetched live from OpenAlex

Abstract Introduction Sexuality is complex and multifaceted, broadly composed of psychological, physiological, interpersonal, identity, and social/political phenomena. The term “sexuality” is used inconsistently in the literature, both in how it is defined by researchers and in how it is measured. Some researchers define sexuality in a narrow, heteronormative, and genital-focused way that negates the subjective experiences of individuals, in turn, affecting how the construct is measured (i.e., measuring sexual function exclusively, overlooking measures of pleasure, self-esteem, and satisfaction). This limited view of sexuality ignores many of the psychosocial and resilience factors that are integral to the construct and results in non-representative measurement tools, especially for equity-seeking groups (i.e., transgender and non-binary (TNB) or intersex individuals provided measures that presume binary anatomy). In order to develop more accurate measurement tools, a comprehensive and inclusive definition of sexuality is warranted. Objective This cross-sectional exploratory survey is the first to formally characterize and define sexuality by assessing how members of the public describe the construct through open-ended questions. Recruitment strategies were aimed towards equity-seeking groups (i.e., sexual and gender minorities, BIPOC, and consensual non-monogamous populations) to ensure the lived experiences of these diverse communities were represented in the definition. Methods A total of 456 individuals (Mage = 28.50, SD = 9.57) identifying as Man (N = 172), Woman (N = 191), Non-Binary (N = 72), Transgender (N = 43), Other (N = 13) were recruited for an online survey asking them to first define sexuality, and then to identify biological, behavioural, psychological, and social components of sexuality. Analyses included a thematic analysis of several open-ended questions. Results Results from a thematic analysis resulted in the following definition of sexuality; Sexuality is a multifaceted concept that is uniquely experienced and expressed. It encompasses a broad range of psychological, physiological, behavioural, and social elements which are experienced to varying degrees. Sexuality is primarily psychological, reflecting one’s emotions, mental state, attractions, desires, fantasies, and identity. Psychological elements of sexuality give meaning to and are expressed via physiological and behavioural elements including objective and subjective bodily reactions, various physical behaviours, and different types of sexual activity. Sexuality is also a social concept, reflected in people’s interactions, relationships, and connections to others. Sexuality is influenced by one’s society and culture, both historically and in present day. Specifically, experiences with norms, taboos, social scripts, and stigma influence one’s sexuality. Conclusions An inclusive definition of sexuality provided by the general public emphasized the importance of psychological components, as well as various physiological, behavioural, and social elements. This demonstrates that the subjective experiences of sexuality are integral to its definition. Therefore, our next step is to generate a comprehensive measure of sexuality that accounts for how diverse people feel about their sexuality. Disclosure No

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)0.059
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.059
Threshold uncertainty score0.311

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.082
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.003
Scholarly communication0.0060.008
Open science0.0010.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.149
GPT teacher head0.426
Teacher spread0.277 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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