Archetypes of Open Science Partnerships: connecting aims and means in open biomedical research collaborations
Bibliographic record
Abstract
Open Science Partnerships (OSPs) are gaining attention as alternatives to university–industry collaborations with restrictive IPR and knowledge sharing policies. OSPs have different expected outcomes and deploy varying means to reach them. Appreciating these differences is crucial to understanding their scientific and socio-economic impact, and yet these differences have never been systematically investigated. This exploratory study draws on qualitative case studies of five biomedical OSPs involving academic partners and pharmaceutical companies. It identifies key elements—purpose, activities and structure—that can be used to describe how OSPs are designed. We identify two key aspects of purpose— predominant intent and research aims —which we argue affect the activities and structure of an OSP. Based on these two aspects, we propose four ideal types of OSPs that are designed to provide a starting point for researchers who explore the nature and impact of OSPs and for practitioners who are developing OSPs and wish to ensure that they deploy appropriate means to meet the intended outcomes of their partnership.
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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 | 0.061 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.016 | 0.066 |
| Scholarly communication | 0.017 | 0.027 |
| Open science | 0.002 | 0.028 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".