Fading vision: knowledge translation in the implementation of a public health policy intervention
Bibliographic record
Abstract
BACKGROUND: In response to several high profile public health crises, public health renewal is underway in Canada. In the province of British Columbia, the Ministry of Health initiated a collaborative evidence-informed process involving a steering committee of representatives from the six health authorities. A Core Functions (CF) Framework was developed, identifying 21 core public health programs. For each core program, an evidence review was conducted and a model core program paper developed. These documents were distributed to health authorities to guide development of their own renewed public health services. The CF implementation was conceptualized as an embedded knowledge translation process. A CF coordinator in each health authority was to facilitate a gap analysis and development of a performance improvement plan for each core program, and post these publically on the health authority website. METHODS: Interviews (n = 19) and focus groups (n = 8) were conducted with a total of 56 managers and front line staff from five health authorities working in the Healthy Living and Sexually Transmitted Infection Prevention core programs. All interviews and focus groups were digitally recorded, transcribed and verified by the project coordinator. Five members of the research team used NVivo 9 to manage data and conducted a thematic analysis. RESULTS: Four main themes emerged concerning implementation of the CF Framework generally, and the two programs specifically. The themes were: 'you've told me what, now tell me how'; 'the double bind'; 'but we already do that'; and the 'selling game.' Findings demonstrate the original vision of the CF process was lost in the implementation process and many participants were unaware of the CF framework or process. CONCLUSIONS: Results are discussed with respect to a well-known framework on the adoption, assimilation, and implementation of innovations in health services organizations. Despite attempts of the Ministry of Health and the Steering Committee to develop and implement a collaborative, evidence-informed policy intervention, there were several barriers to the realization of the vision for core public health functions implementation, at least in the early stages. In neglecting the implementation process, it seems unlikely that the expected benefits of the public health renewal process will be realized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.224 | 0.209 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.014 | 0.044 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.005 | 0.027 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".