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Record W2554461788 · doi:10.1111/cccr.12132

Homosexuality, Moral Panic, and Politicized Homophobia in Ghana: Interrogating Discourses of Moral Entrepreneurship in Ghanaian Media

2016· article· en· W2554461788 on OpenAlexaff
Wisdom J. Tettey

Bibliographic record

VenueCommunication Culture and Critique · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsHomosexualityAntipathySociologyDemocracyPoliticsMoral panicGender studiesPolitical scienceCriminologyLaw

Abstract

fetched live from OpenAlex

The study analyzes media reports about homosexuality in Ghanaian media and the reactions that they engender among the public. It argues that politicized homophobia combined with moral entrepreneurship to produce influential circuits of social, moral, and political power that were deployed to elicit particular forms of subjectivity against homosexuality. The media stimulated and sustained homophobia and heterosexism, and provided a platform for politicians and other moral entrepreneurs to mobilize antipathy in support of reactionary and exclusionary interventions that are antithetical to the very essence of liberal democracy that the country professes. While the media cannot singlehandedly effect value and attitudinal change in support of inclusive citizenship, they have a frontline role in generating critical introspection and dialogic engagement with homosexuality.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.015
Scholarly communication0.0050.004
Open science0.0000.003
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 head0.044
GPT teacher head0.358
Teacher spread0.313 · 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

Citations50
Published2016
Admission routes1
Has abstractyes

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