“Reduce Food Waste, Save Money”: Testing a Novel Intervention to Reduce Household Food Waste
Bibliographic record
Abstract
An intervention, which used elements of the theory of planned behavior, was developed and tested in a randomized control trial (RCT) involving households in the city of London, Ontario, Canada. A bespoke methodology involving the direct collection and measurement of food waste within curbside garbage samples of control ( n = 58) and treatment households ( n = 54) was used to evaluate the effectiveness of the intervention. A comparison of garbage samples before and after the intervention revealed that total food waste in treatment households decreased by 31% after the intervention and the decrease was significantly greater ( p = .02) than for control households. Similarly, avoidable food waste decreased by 30% in treatment households and was also significantly greater ( p = .05) than for control households. Key determinants of treatment household avoidable food waste reduction included personal attitudes, perceived behavioral control, the number of people in a household, and the amount of garbage set out.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".