Cooking habits and skills among college students majoring in Food and Nutrition and Home Economics Education: comparing cooking habits and skills before and after taking cooking practices
Bibliographic record
Abstract
A questionnaire survey was conducted among college students majoring in Food and Nutrition and Home Economics Education with the purpose of investigating how much their understanding about cooking habits and skills had improved with a semester cooking practices. Comparison of the results before and after the cooking practices showed the following educational effects: students were cooking more often and more students had their specialties than before; the number of students who did not know how to make soup stock other than instant one dropped and students acquired Japanese traditional method to make soup stock; the number of students who could prepare fish increased while the number of those who could not decreased; as to fish preparation, students learned the words zeigo (hard scales at the joint of the tail of mackerels) and chiai (dark muscle); a high percentage of students acquired basic techniques to cut food into rounds (wagiri), small pieces from its edge (koguchigiri) and quarter rounds (ichohgiri).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".