<i>Media Training for Diabetes Prevention:</i> A Participatory Evaluation
Bibliographic record
Abstract
The Media and the Message - Promoting Healthy Eating and Active Living for Diabetes Prevention was a project aimed at raising awareness of diabetes risk factors and enhancing the public's access to credible, up-to-date, healthy eating and active living messages in the media. Cross-country workshops were held to teach media strategies and key diabetes prevention messages to multidisciplinary groups of health professionals. Evaluation was integral to the project; both the process and outcomes were assessed using Health Canada's Population Health Approach. Timeline and budget were tracked. Questionnaires were created to evaluate advisory committee conference calls and to determine participants' perceptions of the 19 workshops and resources. A pre-workshop/post-workshop and three-month follow-up questionnaire format, along with an online media-tracking tool, was used to collect outcome data and to measure changes in confidence and media behaviour. Sixty-three percent of participants (150 of 238) reported that multidisciplinary workshops were very valuable. Three-month follow-up revealed a significant increase in confidence in all media activities taught at the workshops, although this failed to translate into increased media activity. Sixty-eight percent (78 of 115) of responding participants disseminated workshop learning. Detailed evaluation revealed that multidisciplinary workshops are valued and effective in increasing confidence. However, eliciting behaviour change following a workshop remains a challenge.
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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 | 0.059 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| 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".