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Record W4402660659 · doi:10.1016/j.clwas.2024.100167

The limitations of an informational campaign to reduce household food waste at the community scale

2024· article· en· W4402660659 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCleaner Waste Systems · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsWestern UniversityPublic Works and Government Services CanadaUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFood wasteScale (ratio)BusinessEnvironmental economicsEconomicsWaste managementEngineeringGeography

Abstract

fetched live from OpenAlex

In this study, we designed and tested a household food waste intervention in the County of Wellington, Canada. This small study compared control households (n = 20) to those receiving an intervention package (n = 32). Food waste generation rates and composition were observed through waste composition audits before and after the intervention, and participants’ feedback on the intervention was received through a survey (n = 7). We found that although the informational campaign was generally not successful in reducing food waste generation at the community scale (possibly due to intention-behavior gaps), there is potential for such interventions to encourage a sub-set of individuals toward reduction behaviors when appropriately targeted and delivered. • An interventional campaign was not effective in reducing household food waste. • Providing information and tips is not enough to change complex wasting behaviors. • Targeted interventions may nudge some individuals toward reduction behaviors.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.075
GPT teacher head0.247
Teacher spread0.171 · 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