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Record W2040639214 · doi:10.1177/2150129711410691

Food Allergy Policy and the Popular Press

2011· article· en· W2040639214 on OpenAlexaffabout
Christen Rachul, Timothy Caulfield

Bibliographic record

VenueJournal of Asthma & Allergy Educators · 2011
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFraming (construction)NewspaperCriticismPublic relationsPublic policyFood allergyMedicinePolitical scienceAllergyImmunologyLaw

Abstract

fetched live from OpenAlex

Issues in policy development for allergy and anaphylaxis have been gaining more attention among both policy makers and the general public. The media can play an important role both in framing allergy issues for the general public and in the policy-making process. As such, an exploration of media representations can provide valuable insight that can inform policy and communication strategies. The authors conducted a content analysis of Canadian newspaper articles to elicit information about the portrayal of laws and policies to address food allergy and anaphylaxis. The authors gathered information on types of policies, support or evidence provided for policies, and whether the overall theme of an article was in support or opposition to a policy. Results indicated that, in general, the media portrayed laws and/or policy proposals to address food allergy-related issues in a supportive manner, but policies that limit individual choice, such as allergy-related food bans, drew more criticism and debate.

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)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.089
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.008
Science and technology studies0.0050.009
Scholarly communication0.0200.006
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0340.002

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 head0.028
GPT teacher head0.292
Teacher spread0.264 · 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 designQualitative
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

Citations8
Published2011
Admission routes2
Has abstractyes

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