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Record W2795708691 · doi:10.1177/1367493518763983

Analysis of sudden infant death syndrome coverage in Canadian newspapers

2018· article· en· W2795708691 on OpenAlexaffabout
Sadia Ahmed, Ian Mitchell, Gregor Wolbring

Bibliographic record

VenueJournal of Child Health Care · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsSudden infant death syndromeNewspaperPublic healthBlameInfant mortalityMedicineEnvironmental healthPediatricsPolitical sciencePsychiatryPopulationNursingLaw

Abstract

fetched live from OpenAlex

Sudden infant death syndrome (SIDS; also known as crib death) describes the sudden unexpected death of an infant under one year of age, which remains unexplained after a thorough investigation. SIDS is a public health concern. It is the fourth leading cause of infant death in Canada. Newspapers are a major source of health information for the public, shape public perceptions and can direct the discussion around issues. Despite the potential influence of newspapers, no study has examined the portrayal of SIDS in Canadian newspapers over time. The purpose of our study was to gain an understanding of SIDS coverage in Canadian English language newspapers using the Canadian Newsstream database from 1970 to 2015 and the historical database: The Globe and Mail from 1844 to 1977. Generating descriptive quantitative and qualitative data, we noted a decline in SIDS coverage over time. Blame and misdiagnosis were two dominant themes in the coverage of SIDS with many other aspects around SIDS missing; for example, indigenous people, who are at higher risk for SIDS, were rarely mentioned. Our findings suggest problems in the content and frequency of coverage of SIDS that have the potential to shape the public understanding of SIDS.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.310
Teacher spread0.292 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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