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Record W2765199182 · doi:10.11114/smc.v5i2.2687

Reframing Fetal Alcohol Spectrum Disorder: Studying Culture to Identify Communication Challenges and Opportunities

2017· article· en· W2765199182 on OpenAlexaboutno aff
Nathaniel Kendall‐Taylor, Marissa Fond

Bibliographic record

VenueStudies in Media and Communication · 2017
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsnot available
Fundersnot available
KeywordsCognitive reframingSalience (neuroscience)Public relationsFetal Alcohol Spectrum DisorderPublic healthSet (abstract data type)Public engagementCulturally appropriateFace (sociological concept)Fetal alcoholSociologyPsychologySocial psychologyPolitical scienceMedicineSocial scienceComputer scienceNursingCognitive psychologyGerontology

Abstract

fetched live from OpenAlex

Implicit cultural understandings challenge those working to increase public awareness and support for programs to prevent and address fetal alcohol spectrum disorder (FASD). Understanding these cultural beliefs reveals key challenges that communicators face; it also helps identify opportunities to foster public engagement and build support for policies and programs that are important for reducing the prevalence of FASD as a public health issue. Through a series of interviews with members of the public in Manitoba, Canada, we identify the cultural models that members of the Manitoban public draw on to make sense of this issue. These models and their implications are used to create a set of recommendations that can improve understanding of the issue, increase issue salience, and generate support for solutions. While the research presented is specific to Manitoba, findings have significance for those working on FASD in other areas and for those working on other public health and science translation projects.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.793
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.138
GPT teacher head0.389
Teacher spread0.251 · 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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