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Record W4402311563 · doi:10.1016/j.appet.2024.107659

Shaping sustainable consumption: Quebec consumers' knowledge and beliefs about the environmental impacts of food

2024· article· en· W4402311563 on OpenAlexaffabout
Laure Saulais, Bertrand Espougne

Bibliographic record

VenueAppetite · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsConsumption (sociology)Sustainable consumptionFood consumptionSustainable agriculturePsychologyBusinessEnvironmental healthSustainabilitySociologyEconomicsAgricultural economicsMedicineEcologySocial science

Abstract

fetched live from OpenAlex

There is growing evidence that shifts in food consumption have the potential to mitigate the environmental impacts of food systems. Yet, although Canadians are increasingly concerned about climate change, changes towards more sustainable food consumption patterns are not widely observed. Understanding consumers' perspective on these issues is crucial for bridging this gap between individual behaviors and collective concerns. This study explores the knowledge, understanding and beliefs of Quebec consumers regarding the environmental impacts of food and their potential for shaping sustainable food consumption. A representative sample of consumers (N = 978) answered an online questionnaire assessing their factual knowledge and investigating their views of food systems impacts. Results indicate low levels of knowledge and highlight widely shared beliefs regarding food systems. Consumers tended to overestimate the role of transport in food's environmental footprint and believe that reducing transport or eating local foods are the most effective ways to improve environmental sustainability. Likewise, consumers tend to underestimate the impact of production, as well as solutions that could effectively reduce this impact. The findings reveal a need for improved literacy and awareness of the environmental impacts of food, thereby highlighting the importance of effective information and education strategies to shape sustainable food consumption habits.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.374

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 communication0.0000.000
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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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 designBench or experimental
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
Published2024
Admission routes2
Has abstractyes

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