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Record W3214928602 · doi:10.3390/su132313218

Increases in Household Food Waste in Canada as a Result of COVID-19: An Exploratory Study

2021· article· en· W3214928602 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsDalhousie University
Fundersnot available
KeywordsFood wasteCoronavirus disease 2019 (COVID-19)Exploratory researchPandemicFood preparationEnvironmental healthBusinessFood processingWaste managementEngineeringMedicineFood scienceSociology

Abstract

fetched live from OpenAlex

The era of the COVID-19 pandemic has resulted in a variety of individual lifestyle and behavioural changes, and could, therefore, potentially involve a shift towards more sustainable food systems. This research was conducted through an online survey of cross-sectional design. We surveyed 8272 Canadians in August of 2020. Participants answered questions about socio-demographic food waste amounts in kilograms, and food-waste-management behaviours. In this exploratory study, we assessed the relationships between socio-demographic variables, and self-reported food-waste behaviours through two-tailed significance testing. Results indicated that Canadian households self-reported an insignificant decrease in food waste during the pandemic. Respondents reported allowing food to expire, not utilizing leftovers, and not finishing meals. Understanding food-waste behaviour changes is key to designing effective mitigation strategies to reduce household food waste and to minimize the environmental consequences with which food waste is associated.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.636
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.034
GPT teacher head0.261
Teacher spread0.227 · 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