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Record W3097411650 · doi:10.1177/1012690220968108

Homo- and transnegativity in sport in Europe: Experiences of LGBT+ individuals in various sport settings

2020· article· en· W3097411650 on OpenAlexaboutno aff
Ilse Hartmann‐Tews, Tobias Menzel, Birgit Braumüller

Bibliographic record

VenueInternational Review for the Sociology of Sport · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
FundersErasmus+
KeywordsSexual orientationTransgenderHeterosexismGender studiesLesbianPsychologyWitnessGender identityMinority stressIdentity (music)Social psychologySociologySexual minorityPolitical science

Abstract

fetched live from OpenAlex

There is broad academic consensus that LGBT+ individuals have been marginalised in both sporting culture and in the academic literature. While the majority of academic research is conducted in the USA, UK, Canada and Australia, the present research is the first to provide a comprehensive picture of the situation and experiences of LGBT+ individuals in sport in Europe based on a quantitative online survey with LGBT+ respondents over 16 years old ( N = 5524). Against the background of a multilevel model for understanding the experiences of LGBT+ individuals and the minority stress model, this article focuses on two questions: firstly, if, and to what extent, LGBT+ individuals witness or experience homo-/transnegative episodes in sport and, secondly, whether they refrain from participating in sport and/or feel excluded from specific sports due to their sexual orientation and/or gender identity. The analysis takes into account diverse intersections of sexual orientation and gender identities within the umbrella of LGBT+ and different sport contexts that reflect the broad scope of sport cultures. Data reveal that non-cisgender persons make up the most vulnerable group within the umbrella of LGBT+ and that there is an inverse relation of distal/proximal stressors with regard to experiences of homophobic language in different sport contexts.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.039
GPT teacher head0.345
Teacher spread0.306 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2020
Admission routes1
Has abstractyes

Explore more

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