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Record W2897205743 · doi:10.1017/s1368980018002550

Do manufacturer ‘nutrient claims’ influence the efficacy of mandated front-of-package labels?

2018· article· en· W2897205743 on OpenAlexafffundabout
Rachel B. Acton, David Hammond

Bibliographic record

VenuePublic Health Nutrition · 2018
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health ResearchUniversity of WaterlooPublic Health AgencyPublic Health Agency of Canada
KeywordsNutrientProduct (mathematics)Task (project management)BusinessPsychologyBiologyMathematicsEconomicsEcology

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine consumers' ability to correctly interpret front-of-package (FOP) 'high in' warnings in the presence of a voluntary claim for the same or a different nutrient. DESIGN: A between-group experimental task assigned respondents to view food products labelled as 'high in sodium', with a 'reduced sodium' claim positioned next to the warning, away from the warning or absent. A second experiment assigned participants to view a food product labelled as 'high in sugar', with a 'reduced fat' claim positioned next to the warning, away from the warning or absent. For both tasks, respondents were asked to identify whether the products were high in the indicated nutrient. SETTING: Online survey (2016). SUBJECTS: Canadians aged 16-32 years (n 1000) were recruited in person from five major cities in Canada. RESULTS: Respondents were less likely to correctly identify a product as 'high in sodium' when packages also featured a voluntary 'reduced sodium' claim, with a stronger effect when the claim was positioned away from the FOP symbol (P<0·001). The number of correct responses was similar across conditions when the nutrient claim was for a different nutrient than the one featured in the FOP 'high in' warning. CONCLUSIONS: The findings demonstrate that the presence of a voluntary nutrient claim can undermine the efficacy of mandated FOP labels for the same nutrient. Countries considering nutrient-specific FOP warnings, including Canada, should consider regulations that would prohibit claims for nutrients that exceed the threshold for nutrient-specific FOP warnings.

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)0.000
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 score0.632
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.039
GPT teacher head0.332
Teacher spread0.294 · 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

Citations34
Published2018
Admission routes3
Has abstractyes

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