Is this too ugly for you?
Bibliographic record
Abstract
Background: Globally 1.3 billion tonnes of food are wasted every year equating to approximately 750 billion US dollars (1). In Canada it has been estimated that $31 billion of food is wasted annually (2). This amount can easily be used to feed hundreds of thousands of undernourished people across the world. Food wastage can occur at every level of the food supply chain. The purpose of this study was to evaluate the food waste generated by residents of British Columbia, Canada. The study aimed to identify the general knowledge regarding food waste and ugly produce, the attitudes of the public towards food waste, and the general practices of waste disposal. Methods: A self-administered electronic survey created on Survey Monkey Canada was distributed on various social media platforms over a two-week period in January 2020. The survey contained questions that resulted in a score for knowledge of food waste, attitude towards food waste and the waste reduction practices of British Columbian residents. Chi square and correlational analyses were performed using the statistical package NCSS. Results: 96 respondents met the inclusion criteria and completed the survey. Many participants received a medium score for knowledge (N=67) and possessed a positive attitude (N=71) towards food waste. There was an even distribution between good and fair practice level (N=49 and N=46). There was no association between level of food waste knowledge and demographic categories except for age (p=0.025). Younger participants were less knowledgeable. Between practice and demographic variables, no statistically significant associations were found. The results for attitude were determined to be non-statistically significant for age, gender and experience working in the food industry while there was a statistically significant association between attitude and an individual’s education level (p = 0.008). Those with higher levels of education had a more positive attitude. No correlation was determined between knowledge and practice indicating that there is no influence of knowledge on practice and vice versa. The study found that there is a positive correlation (p = 0.0004 and r = 0.3542) between attitude and practice indicating that these two variables influence each other. Conclusion: This study demonstrated that the population in B.C. who responded to the survey has adequate knowledge, a positive attitude and moderate practice behaviours regarding food waste. Younger individuals were less knowledgeable about food waste and the more educated one is, the more positive their attitude towards food is. The study also indicated that positive attitudes translated into better practice. These results are only a starting point in determining the causes for food loss and waste in B.C as it reveals the need for more local initiatives to bring everyone to start adopting food waste reduction strategies.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".