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Record W3117134335 · doi:10.1108/bfj-04-2020-0307

Meat reduction, vegetarianism, or chicken avoidance: US omnivores’ impressions of three meat-restricted diets

2020· article· en· W3117134335 on OpenAlexaff
Kathryn Asher, Paul A. Peters

Bibliographic record

VenueBritish Food Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsCarleton UniversityUniversity of New Brunswick
Fundersnot available
KeywordsOmnivorePerceptionConsumption (sociology)Food scienceAffect (linguistics)Red meatBiologyPsychologyCommunicationEcologySociologySocial science

Abstract

fetched live from OpenAlex

Purpose Meat consumption has a variety of implications in society. While various types of meat-restricted diets exist to address this, not enough is known about how the average meat consumer views different avenues to lessening their intake. In response, this study aims to assess US omnivores’ impressions of three meat-restricted diets. Design/methodology/approach An online survey was administered to a cross-sectional, census-balanced sample from Nielsen of 30,000+ US adults. Omnivores ( N = 928) were randomized into one of the three conditions where they were asked about their perceptions of a vegetarian diet, a reduced-meat diet or a chicken-free diet as individuals not currently following that dietary pattern. Findings The findings showed that omnivores had a more favorable perception of a reduced-meat diet on a greater number of study variables as compared to the vegetarian or chicken-free diets. The research also demonstrated that a majority of omnivores were in the precontemplation stage of cognitive change, suggesting that most American omnivores are not actively demonstrating a readiness to alter their meat consumption in the ways presented. Originality/value This research is the first to examine the comparative trends around these three diets among omnivores. It also speaks to how the desirability of meat restriction varies by type of approach, i.e. elimination or reduction, and if the latter, what type. The findings may be of relevance for efforts to reduce global meat consumption for ethical, health, or environmental reasons.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.213
Teacher spread0.197 · 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.

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

Citations6
Published2020
Admission routes1
Has abstractyes

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