Improving cooking skills and confidence
Bibliographic record
Abstract
Improving cooking skills and confidenceA recent study reported that parents serve prepackaged, processed meals to their family, not only for reasons of convenience, but also due to lower self-efficacy for cooking and decreased ability to plan meals [1].Programs targeting children may help to address this situation.In this issue of the Journal, Zahr and Sibeko report on the outcomes of a cooking and tasting program offered in schools, designed to help children gain knowledge and enjoyment from food and develop cooking skills.A quasi-experimental design collected information from grade 4 and 5 students who participated in the program compared to those who did not.The preliminary results suggest that improvements in food preferences for specific foods, skills, and cooking confidence can be achieved in preadolescents who participated in the program, and this translated to behavioural changes at home.This evaluation provides support for dietitians to collaborate with schools to develop and deliver similar hands-on programs.At this time of year, we should all be aware of the 2017 nutrition month slogan, "Take the fight out of food!Spot the problem.Get the facts.Seek support."(www.nutritionmonth2017.ca).The resources and fact sheets provide evidence-based information and links to reputable websites and support to help Canadians end their struggles with food.I would like to take this opportunity to formally acknowledge and extend my sincere appreciation to those individuals in 2016 who volunteered their time and expertise to review submissions to the Journal (see list of reviewers for 2016 http://dcjournal.ca/page/ reviewers-cjdpr).The volunteer peer review process maintains the high quality of published articles relevant to Canadian dietitians.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".