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Record W2903195860 · doi:10.15353/cjds.v7i3.452

Stereotyping and Stigmatising Disability: A Content Analysis of Canadian Print News Media About Fetal Alcohol Spectrum Disorder

2018· article· en· W2903195860 on OpenAlexafffundvenueabout
John Aspler, Natalie Zizzo, Nina Di Pietro, Éric Racine

Bibliographic record

VenueCanadian Journal of Disability Studies · 2018
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsMcGill UniversityDouglas CollegeUniversité de MontréalMontreal Clinical Research Institute
FundersCanadian Institutes of Health ResearchKids Brain Health NetworkMcGill University
KeywordsShameBlameFetal Alcohol Spectrum DisorderStigma (botany)NewspaperPsychologyNarrativeFetal alcoholContent analysisMedia coveragePsychiatrySocial psychologyPregnancySociologyMedia studies

Abstract

fetched live from OpenAlex

People with fetal alcohol spectrum disorder (FASD), a complex and controversial neurodevelopmental disability caused by alcohol exposure in the womb, report experiences of stigma in different parts of their lives. The media, sometimes central to how a public understands and constructs marginalized identities, have a notable history of poorly representing people with disabilities like FASD (including in Canada), which could increase their stigmatisation. Additionally, given its cause, women who drink while pregnant can also face stigmatisation – with some public discourses evoking narratives that promote blame and shame. To gain insight into the kinds of information presented to Canadians about FASD, alcohol, and pregnancy, we conducted a media content analysis of 286 articles retrieved from ten of the top Canadian newspapers (2002-2015). In this article, we report key themes we identified, most common being ‘crime associated with FASD’. We explore connections between this coverage, common disability stereotypes (i.e., criminal behaviour and ‘the villain’), FASD stigma, and expectations of motherhood.

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)0.004
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.406
Threshold uncertainty score0.816

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0140.019
Science and technology studies0.0070.005
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.072
GPT teacher head0.307
Teacher spread0.235 · 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 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

Citations22
Published2018
Admission routes4
Has abstractyes

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Same venueCanadian Journal of Disability StudiesSame topicPrenatal Substance Exposure EffectsFrench-language works237,207