Reflections on Co-Production as a Mode of Knowledge Production; Comment on "Research Coproduction: An Underused Pathway to Impact"
Bibliographic record
Abstract
Rycroft-Malone and colleagues' editorial on research co-production highlights the potential of a co-production mode of research to narrow the gap between knowledge production and use. This commentary critiques implicit assumptions within the argument and challenges the view that traditional (Mode 1) science bears the primary responsibility for delayed implementation and questions the inherent superiority of co-production. It also highlights the importance of political and policy considerations in considering research uptake. "Mode 3" knowledge production (integrating Modes 1 and 2 discovery) offers a potentially more advanced framework that recognizes systems and organizational perspectives. A deeper, multi-layered exploration of the influence of socio-political and policy contexts is needed to understand the full potential of co-production on knowledge utilization.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Editorial About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | MetaresearchScience and technology studies Domain: Methods · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.034 | 0.141 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.055 | 0.054 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".