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Record W2520062310 · doi:10.1080/15299716.2016.1227016

Defining Bisexuality: Young Bisexual and Pansexual People's Voices

2016· article· en· W2520062310 on OpenAlexaff
Corey E. Flanders, Marianne LeBreton, Margaret Robinson, Jing Bian, Jaime Alonso Caravaca‐Morera

Bibliographic record

VenueJournal of Bisexuality · 2016
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of TorontoDalhousie UniversityMcGill University
Fundersnot available
KeywordsContext (archaeology)PsychologySocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Bisexuality is defined in a plethora of ways, including definitions based on behavior, attraction, or desire and may employ binary or nonbinary definitions. Research has not adequately addressed how young bisexual people themselves define bisexuality, whether those definitions change with social context, or whether bisexual people define bisexuality differently from pansexual people. The current study addresses these questions through an online, mixed-methods study. A total of 60 bisexual and pansexual participants aged ages 18 to 30 responded to closed- and open-ended questions regarding their definitions of bisexuality. Closed-ended responses were analyzed with a series of chi-square tests, while we conducted a summative content analysis on the open-ended responses. Results indicate that in general, bisexual and pansexual people define bisexuality similarly. Participants modified their definitions of bisexuality depending upon the social context. Implications for research are discussed.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0050.006
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.393
Teacher spread0.344 · 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 designQualitative
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

Citations89
Published2016
Admission routes1
Has abstractyes

Explore more

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