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Record W4283265881 · doi:10.1002/fes3.405

The future of sustainable food consumption in China

2022· article· en· W4283265881 on OpenAlex
May Chu, Sven Anders, Qing Deng, Carolina A. Contador, Francisco Cisternas, Catherine Ann Caine, Zhu Ying, Shuyuan Yang, Bo Hu, Zhiguang Liu, Lap Ah Tse, Hon‐Ming Lam

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

VenueFood and Energy Security · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversity of Alberta
FundersChinese University of Hong Kong
KeywordsSustainable consumptionChinaBusinessConsumption (sociology)Theory of planned behaviorGovernment (linguistics)Sustainable developmentSustainable agricultureConceptual frameworkGreenhouse gasMarketingConstruct (python library)PopulationSustainabilityEnvironmental economicsControl (management)Production (economics)EconomicsPolitical scienceSociology

Abstract

fetched live from OpenAlex

Abstract Food production is one of the main contributors to greenhouse gas emissions and climate change. China, as a rapidly developing economy, contributes to an unsustainable food system as its consumption of animal products and meat has continued to grow in recent decades. Using the extended theory of planned behavior as the conceptual framework, this paper examines factors influencing consumers' intention to purchase sustainable food in China. To this end, a population‐based face‐to‐face survey was conducted with 2422 respondents in five provinces spanning the north and south of China. The results showed that the traditional constructs of behavioral attitude, subjective norms, perceived behavioral control, and the additional construct of perceived quality are significant in inducing such intentions. This paper suggests that to enhance consumers' willingness to shift to sustainable food consumption, appropriate regulation and monitoring framework is needed to increase consumers' trust toward sustainable food. The government can also cooperate with the media, experts, and social media opinion leaders to ensure that messages on sustainable development are promoted in effective ways.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.351

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 science0.0000.001
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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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