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Record W2049488729 · doi:10.1080/13698575.2014.966806

The role of the media in construction and presentation of food risks

2014· article· en· W2049488729 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Risk & Society · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsConstruct (python library)Presentation (obstetrics)Risk societyMass mediaPublic relationsFood safetyPerspective (graphical)BusinessMarketingAnxietyAdvertisingPsychologyPolitical scienceSociologyMedicineComputer scienceSocial science

Abstract

fetched live from OpenAlex

In this article we examine how and why the media construct food risks, from the perspective of ‘media actors’ (people involved in different types of media) using data from 30 interviews conducted in 2013 with media actors from Australia and the United Kingdom. In modern society, many risks are invisible and are brought to the attention of the public through representations in the mass media. This is particularly relevant for food safety, where the widening gap between producers and consumers in the developed world has increased the need for consumer trust in the food supply. We show the importance of newsworthiness in construction of media stories about food risk using Beck’s ideas on cosmopolitan risk to interpret the data. We note the ways in which the strategies that media actors use to construct stories about food risk amplify the risk posed potentially creating consumer anxiety about the safety of the food system. It is important for food regulators and public health professionals to be aware of this anxiety when presenting information about a food incident so that they can target their message accordingly to decrease anxiety.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.028
GPT teacher head0.346
Teacher spread0.318 · 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