Knowledge Exchange Processes in Organizations and Policy Arenas: A Narrative Systematic Review of the Literature
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
CONTEXT: This article presents the main results from a large-scale analytical systematic review on knowledge exchange interventions at the organizational and policymaking levels. The review integrated two broad traditions, one roughly focused on the use of social science research results and the other focused on policymaking and lobbying processes. METHODS: Data collection was done using systematic snowball sampling. First, we used prospective snowballing to identify all documents citing any of a set of thirty-three seminal papers. This process identified 4,102 documents, 102 of which were retained for in-depth analysis. The bibliographies of these 102 documents were merged and used to identify retrospectively all articles cited five times or more and all books cited seven times or more. All together, 205 documents were analyzed. To develop an integrated model, the data were synthesized using an analytical approach. FINDINGS: This article developed integrated conceptualizations of the forms of collective knowledge exchange systems, the nature of the knowledge exchanged, and the definition of collective-level use. This literature synthesis is organized around three dimensions of context: level of polarization (politics), cost-sharing equilibrium (economics), and institutionalized structures of communication (social structuring). CONCLUSIONS: The model developed here suggests that research is unlikely to provide context-independent evidence for the intrinsic efficacy of knowledge exchange strategies. To design a knowledge exchange intervention to maximize knowledge use, a detailed analysis of the context could use the kind of framework developed here.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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