Examining the portrayal of homophobic and non-homophobic aggression in print media through an integrated grounded behavioural linguistic inquiry (IGBLI) approach
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".