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Record W2539751121 · doi:10.1080/00918369.2016.1236592

Positive Identity Experiences of Young Bisexual and Other Nonmonosexual People: A Qualitative Inquiry

2016· article· en· W2539751121 on OpenAlexaff
Corey E. Flanders, Lesley A. Tarasoff, Melissa Marie Legge, Margaret Robinson, Giselle Gos

Bibliographic record

VenueJournal of Homosexuality · 2016
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsOntario HIV Treatment NetworkMcMaster UniversityPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsQualitative researchIdentity (music)PsychologyHomosexualityGender studiesSexual identityHeteronormativitySociologySocial psychologyHuman sexualityDevelopmental psychologyAnthropology

Abstract

fetched live from OpenAlex

The majority of LGBTQ psychological research focuses on dysfunction. The exclusion of strengths-based perspectives in LGBTQ psychology limits the understanding of LGBTQ mental health. In this article we report experiences that young bisexual and other nonmonosexual people perceive as affirming of their sexual identity. A 28-day, daily diary study was used to investigate whether bisexual-identified participants encountered positive experiences related to their sexual identity, and which type of experiences they perceived to be positive. Using a constructivist grounded theory approach, participants' experiences were organized according to a social ecological model. Experiences were reported at the intrapersonal, interpersonal, and institutional levels, but most positive sexual identity experiences occurred at the interpersonal level. Implications for positive health outcome research and the integration of positive psychology with LGBTQ psychology are discussed, as well as study limitations.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.005
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.106
GPT teacher head0.479
Teacher spread0.374 · 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

Citations55
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of HomosexualitySame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207