Bridging the ‘Two Cultures’ of Research and Service: Can Complexity Theory Help? Comment on "Experience of Health Leadership in Partnering With University-Based Researchers in Canada – A Call to ‘Re-imagine’ Research"
Bibliographic record
Abstract
This commentary addresses Bowen et al's empirical study of perspectives of Canadian healthcare staff towards research and their call for multi-faceted action to improve misalignments in the system. This commentary argues that tensions and misalignments between research and service are inherent and can never be eradicated. Building on previous work by Lanham et al, I propose seven principles of complexity which may help to develop system capacities that will help bridge the research-service gap: acknowledge unpredictability, recognise selforganisation, facilitate interdependencies, encourage sensemaking, attend to human relationships, develop adaptive capabilities in staff, and harness conflict productively.
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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 | 0.018 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.015 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.056 | 0.056 |
| Insufficient payload (model declined to judge) | 0.007 | 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, 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".