Developing a Tool to Measure Knowledge Exchange Outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: This article describes the process of developing measures to assess knowledge exchange outcomes using the dissemination of a best practices in type 2 diabetes document as a specific example. A best practices model consists of knowledge synthesis, knowledge exchange (dissemination/adoption), and evaluation stages. Best practices are required at each stage. An extensive literature review found no previous knowledge syntheses of concrete tools and models for evaluating dissemination or exchange strategies. This project developed a practical and usable tool to measure the reach and uptake of disseminated innovations. The instrument itself facilitates an opportunity for knowledge exchange to occur between producers and adopters. At this point the tool has a strong theoretical basis. Initial pilot-testing has begun; however, the accumulation of evidence of validity and reliability is only in the planning stages. The instrument described here can be adapted to other areas of population health and evaluation research.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it