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Record W2602596225 · doi:10.1108/jfp-02-2017-0003

Examining the portrayal of homophobic and non-homophobic aggression in print media through an integrated grounded behavioural linguistic inquiry (IGBLI) approach

2017· article· en· W2602596225 on OpenAlexaboutno aff
Philip Birch, Rebecca Ozanne, Jane L. Ireland

Bibliographic record

VenueJournal of Forensic Practice · 2017
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperOriginalityAggressionContent analysisPsychologyRepresentation (politics)Grounded theorySocial mediaSocial psychologySociologyMedia studiesSocial scienceQualitative researchComputer sciencePolitical scienceCreativity

Abstract

fetched live from OpenAlex

Purpose The role of the media in supporting an understanding of the social world is well documented. The representation of homosexuals in the media can therefore impact on homophobia within society. The purpose of this paper is to examine how homosexuals are portrayed in the media generally, before examining and comparing newspaper reports of homosexual aggression with heterosexual aggression. Design/methodology/approach Utilising a new and innovative research methodology, an integrated grounded behavioural linguistic inquiry (IGBLI) approach, four daily newspapers in circulation within the USA, Canada, the UK and Australia are examined. Findings While there are similarities in the way print media report on these aggressive incidents, the differences which emerge from the findings are of interest which require further, more in-depth study. Practical implications To extend the methodology of IGBLI to other forms of media content in order to further validate the approach. To reduce the differences between LGBTI news reports and heterosexual news reports. To hold the media to account for the ways in which they express their content. To encourage users of the media, in particular print media, to be critical of what they read. Originality/value Typically, analysis of media utilises the research method of content analysis. This paper adopts a new and innovative research method, an IGBLI approach, which incorporates a behavioural assessment in the form of a SORC.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.314
Teacher spread0.245 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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