Exploring convenience orientation as a food motivation for college students living in residence halls
Bibliographic record
Abstract
Abstract The main objective of this paper is to study the concept of convenience orientation among young adults. A project was conducted among students living in residence halls, where information on their food motivation and behaviour was obtained. Data were collected using a self‐administered questionnaire filled out by 319 students. Convenience ap‐pears to be the most important food motivation followed by price, pleasure, health and concern about weight. Positive correlations were obtained between convenience and: deciding what to eat, having a varied diet and lack of time, all of which were considered to be difficulties associated with living in residence. Negative correlations were obtained between convenience and total time spent cooking per day and having learned to be autonomous in the kitchen. For male, the perception of eating well, having a varied diet, and maintaining weight were negatively correlated to convenience. For female, the correlation between convenience and the difficulty of eating enough was significant and positive. Negative correlations were obtained between convenience and fresh vegetables, potatoes, eggs, fresh meat, fresh fish and fresh poultry, herbal tea and alcohol. Positive correlations were obtained between convenience, frozen foods and foods brought from the parents’ home. Findings are discussed from both a health and a family perspective.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".