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Record W3039061493 · doi:10.1080/17512786.2020.1786436

Justice Reframed? A Comparative Critical Discourse Analysis of Twitter Campaigns and Print Media Discourse on Two High-Profile Sexual Assault Verdicts in Ireland and Spain

2020· article· en· W3039061493 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournalism Practice · 2020
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsCritical discourse analysisMainstreamSociologyFraming (construction)Frame analysisMedia studiesDiscourse analysisSocial mediaGender studiesCriminologyPoliticsLawContent analysisSocial sciencePolitical scienceIdeologyHistory

Abstract

fetched live from OpenAlex

Analyses of media discourses on judicial verdicts in sexual violence cases offer critical insight into how this topic is mediated. This study explores post-verdict mainstream and social media reaction to two high-profile verdicts in sexual assault cases in Ireland and Spain: #IBelieveHer, launched in March 2018 following the acquittal of four men accused of rape in Belfast, and #YoTeCreo which coalesced online after five men were given a lesser sentence for sexual abuse in Pamplona in April 2018. This study first identifies the stance taken by mainstream media where verdicts were contrary to “popular” opinion. Secondly, it analyses dominant hashtags that emerged on Twitter following both verdicts. Finally, it traces similarities and differences in discourse patterns identified on mainstream and social media platforms across both countries. For analysis, we employed a Critical Discourse Analysis-based theoretical framework (e.g.,KhosraviNik 2017 KhosraviNik, M. 2017. “Social Media Critical Discourse Studies (SM-CDS).” In Handbook of Critical Discourse Analysis, edited by J. Flowerdew and J.E. Richardson, 583–596. London: Routledge.[Crossref] , [Google Scholar], “Social Media Critical Discourse Studies (SM-CDS).” In Handbook of Critical Discourse Analysis, 582–596) with resources from Framing Analysis (e.g.,Goffman 1974 Goffman, E. 1974. Frame Analysis: An Essay on the Organization of Experience. Vancouver: Harvard University Press. [Google Scholar], Frame Analysis: An Essay on the Organization of Experience. Vancouver: Harvard University Press) for methodological purposes. Findings suggest Spanish print media contained greater debate around legal understandings of sexual violence while the Spanish Twitter campaign was outward-oriented and explicitly feminist. #IBelieveHer displayed a narrower focus, with the “celebrity” dimension to this case contributing to a personalised, less nuanced, discourse on social and print media and more polarised discussion.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.058
GPT teacher head0.378
Teacher spread0.321 · 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