Bibliographic record
Abstract
Purpose The purpose of this study is to provide information relating to organic food consumption patterns specific to the Canadian population and youth demographic. The primary objective of this pilot study is to investigate the knowledge, consumption patterns and willingness to pay for organic food among the first-year University students enrolled in courses at Brescia University College. Design/methodology/approach A questionnaire has been developed by the researchers and distributed to several first-year classes at Brescia University College. The results have been analyzed using Wilcoxon scores (rank sums), Wilcoxon two-sample test, Spearman correlation coefficients and univariate and multivariate regression analyses. A theme analysis has been generated from open-ended questions. Findings No significant differences exist between nutrition and non-nutrition students. Attitudes toward organic food and knowledge score significantly impact the consumption patterns and willingness to pay for organic food (p = < 0.0001). Most students indicated that they were willing to pay a premium for organic food and had positive associations with it. Originality/value This is the first study relating to this topic and the Canadian population. Results from this study provide baseline data that may be used to conduct future research.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".