The ‘wonderfulness’ of children’s feeding programs
Bibliographic record
Abstract
When people involved in children's feeding programs were asked to describe them, without exception they were described using phrases that reflected the perception of 'wonderfulness'. This paper critically analyses the 'wonderfulness' of children's feeding programs by examining the language used to describe these programs, and the features of a 'wonderful' program through an analysis of a multi-site, qualitative case study of nine diverse programs in Atlantic Canada. When participants justified their comments about the 'wonderfulness' of children's feeding programs, they did so based upon five perceptions of program strengths: enhanced family coping; providing good food and nutrition; socializing and making friends; behaving well in school; and volunteerism. We suggest that programs can be designed to be innately 'wonderful' if they are community- and charity-based, support a noble cause such as the elimination of child hunger, engage good people as donors and volunteers, and provide a direct service to children apart from their families. We challenge health promoters to beware of the 'wonderful' program; its 'wonderfulness' may actually be masking unintended negative impacts upon its participants.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".