What are the Practices Around Fast-Food Consumption at the University of Saskatchewan?
Bibliographic record
Abstract
Fast-food is an easily accessible and predominant part of social and food culture.Fast-food often contains high fat, salt, and sugar contents which may be a contributor to weight gain in today's society.• In 2019, the average Canadian household spent onequarter of its food budget on meals from restaurants (Polsky & Garriguet, 2021).• In the transition from high school to college, student diets often worsen (fast-food being a possible contributor), which leads to significant changes in weight after the first year of university (Grace, 1997), (Anderson et al., 2003), (Deshpande et al., 2009).• In 2010, a study from a U.S. university surveyed many students where 84% consumed fast-food and 54% of them at least once a week (Haines et al. 2010).• Few studies have been conducted on fast-food consumption in Canadian University populations.• As students at the University of Saskatchewan, we are interested in the consumption habits of fast-food by all campus members.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".