Developing and Testing a Novel Intervention to Reduce Household Food Waste
Bibliographic record
Abstract
The amount of food wasted is a topic of societal and academic interest. As academic research in this area is nascent, there are significant knowledge gaps, which this dissertation seeks to narrow, pertaining to: (1) the measurement of food waste; (2) the human behaviors that lead to wasting of food; and (3) the development of efficacious food waste reduction interventions.\nA systematic literature review of 55 food waste estimates showed that on average 114.3 kg/capita/year is wasted from consumption (i.e., household) and 198.9 kg/capita/year across the entire food supply chain. There is considerable uncertainty with this data because of the different food waste measurements methodologies employed.\nHousehold waste composition study data (2012-2015) from 9 Ontario municipalities, that used the same direct measurement methodology and included a single “food waste” category, were aggregated and analyzed to develop estimates of food waste in the garbage stream. This methodology, which showed households disposed 2.40 kg/week of food waste in the garbage, was used as the basis of a bespoke household food waste measurement methodology.\nTo better understand food wasting behavior and facilitate the development of an effective intervention the theory of planned behavior (TPB) was used to inform the development of a survey, which was administered to households in London, Ontario, Canada. Households (n=1,263) threw out avoidable food 4.8 times/week and perceived behavioral control (p\nA “Reduce Food Waste, Save Money” household intervention, which combined elements of behavioral economics (nudging the desire to reduce monetary loss) and the TPB (strengthening perceived behavioral control), was developed, tested and assessed in a randomized control trial. Treatment total household food waste decreased by 31% and this was significantly greater (p=0.02) than for control households. Key determinants of avoidable food waste reduction included personal attitudes, perceived behavioral control, the number of people in a household and the amount of garbage set out.\nThis research can contribute directly to food waste reduction policy in national, provincial, and municipal contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".