From Evidence-Based Practice Making to Practice-Based Evidence Making
Bibliographic record
Abstract
Models of research translation frequently emphasize independent roles for research producers and intended users. This article describes a novel approach for enhancing exchange between researchers and practitioners. The framework is based on Wenger's notion of Communities of Practice (CoP) where knowledge is regarded as a social enterprise at the center of member interactions. Research-based practices and policies emerge when research producers and users mutually engage one another about specific health promotion problems through negotiation and by creating and sharing technical standards and other resources. CoPs are more than loose networks or task-oriented teams. They aim to create both social and intellectual capital through mutual negotiation, reciprocity, trust, and cohesion. A Consortium of Quitline Operators across North America and a Canadian project to enhance research capacity for tobacco control research serve as examples of how the model has been successfully operationalized.
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 | 0.412 | 0.371 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.009 | 0.114 |
| Scholarly communication | 0.041 | 0.044 |
| Open science | 0.012 | 0.036 |
| Research integrity | 0.017 | 0.023 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".