<i>Empowerment Evaluation in Redesigning</i> A Public Health Unit Nutrition Program
Bibliographic record
Abstract
This article illustrates how empowerment evaluation was used in Toronto Public Health's (TPH) nutrition programming redesign to consult with staff about how roles, responsibilities, and organisational structure could be changed to improve how nutrition programs are delivered. One of three moderators facilitated the ten two-hour focus group sessions in TPH. TPH staff, namely 71 front-line staff and 13 managers who were responsible for providing community nutrition services, participated in the study. Focus group participants included Public Health Dietitians, Public Health Nutritionists, Public Health Nurses (PHNs), and paraprofessionals (i.e., community nutrition assistants). Participants' preferred roles, responsibilities, and organisational structure in TPH, which they believe would improve nutrition service delivery in the community, were examined. A constant comparison approach was used to develop themes inductively. It was found that participants wanted Dietitians and Nutritionists to provide current nutrition-related information to them. They felt that nutrition programs should be promoted better and made more accessible to the public. They suggested that Dietitians and Nutritionists and other staff should share information with each other better. They suggested that Dietitians and Nutritionists should provide nutrition services directly to the public and provide support to other staff, mainly PHNs, who deliver nutrition programs. In conclusion, this empowerment evaluation produced results that were used to assist in decision making about nutrition programming.
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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 | 0.030 | 0.026 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".