Cook It Up! A community-based cooking program for at-risk youth: overview of a food literacy intervention
Bibliographic record
Abstract
BACKGROUND: In Canada, there are limited occasions for youth, and especially at-risk youth, to participate in cooking programs. The paucity of these programs creates an opportunity for youth-focused cooking programs to be developed, implemented, and evaluated with the goal of providing invaluable life skills and food literacy to this potentially vulnerable group. Thus, an 18-month community-based cooking program for at-risk youth was planned and implemented to improve the development and progression of cooking skills and food literacy. FINDINGS: This paper provides an overview of the rationale for and implementation of a cooking skills intervention for at-risk youth. The manuscript provides information about the process of planning and implementing the intervention as well as the evaluation plan. Results of the intervention will be presented elsewhere. Objectives of the intervention included the provision of applied food literacy and cooking skills education taught by local chefs and a Registered Dietitian, and augmented with fieldtrips to community farms to foster an appreciation and understanding of food, from 'gate to plate'. Eight at-risk youth (five girls and three boys, mean age = 14.6) completed the intervention as of November 2010. Pre-test cooking skills assessments were completed for all participants and post-test cooking skills assessments were completed for five of eight participants. Post intervention, five of eight participants completed in-depth interviews about their experience. DISCUSSION: The Cook It Up! program can provide an effective template for other agencies and researchers to utilize for enhancing existing programs or to create new applied cooking programs for relevant vulnerable populations. There is also a continued need for applied research in this area to reverse the erosion of cooking skills in Canadian society.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".