Protecting the Paradox of Interprofessional Collaboration
Bibliographic record
Abstract
We studied an interprofessional collaboration to understand how professionals engaged with paradox in collective decision-making. At the beginning of our study, we observed vicious cycles in which conflict led to negative tension. Professionals were holding tightly to a particular pole of the paradox, and the higher-status pole was consistently overrepresented in collective decision-making. By the end of our study we observed the presence of virtuous cycles, where conflict led to more positive tension, and where professionals engaged in collective decision-making with more equal representation of conflicting approaches. We call this change process protecting the paradox and we identify three strategies that support this process: (1) promoting equality of both poles, (2) strengthening the weaker pole, and (3) looking beyond the paradox by focusing on desired outcomes. We contribute to the paradox literature by showing how vicious cycles can be shifted to virtuous cycles, how professionals and managers can work together to protect a paradox, and how status differences between poles can be redistributed.
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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 | 0.026 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.022 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".