Perceptions of the characteristics of the<scp>A</scp>lberta<scp>N</scp>utrition<scp>G</scp>uidelines for<scp>C</scp>hildren and<scp>Y</scp>outh by child care providers may influence early adoption of nutrition guidelines in child care centres
Bibliographic record
Abstract
In 2008, the Alberta government released the Alberta Nutrition Guidelines for Children and Youth (ANGCY) as a resource for child care facilities to translate nutrition recommendations into practical food choices. Using a multiple case study method, early adoption of the guidelines was examined in two child care centres in Alberta, Canada. Key constructs from the Diffusion of Innovations framework were used to develop an interview protocol based on the perceived characteristics of the guidelines (relative advantage, compatibility, complexity, trialability and observability) by child care providers. Analysis of the ANGCY was conducted by a trained qualitative researcher and validated by an external qualitative researcher. This entailed reviewing guideline content, layout, organisation, presentation, format, comprehensiveness and dissemination to understand whether characteristics of the guidelines affect the adoption process. Data were collected through direct observation, key informant interviews and documentation of field notes. Qualitative data were analysed using content analysis. Overall, the guidelines were perceived positively by child care providers. Child care providers found the guidelines to have a high relative advantage, be compatible with current practice, have a low level of complexity, easy to try and easy to observe changes. It is valuable to understand how child care providers perceive characteristics of guidelines as this is the first step in identifying the needs of child care providers with respect to early adoption and identifying potential educational strategies important for dissemination.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".