The pragmatic cycle of knowledge work: Unlocking cross-domain collaboration in open innovation spaces
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
Collaborating is increasingly characterized by working across domains and organizations. Teams rapidly form and dissolve, actors and settings frequently change, yet most academic research focuses on stable organizations and team configurations with familiar domains. This leads to the question: how do people successfully collaborate across domains and organizations in circumstances where there is little shared knowledge? We explored this question within the nascent digital health sector when Hacking Health-a non-profit organization-used an open innovation approach to bring together actors from different domains and organizations in temporary spaces to spur new collaborations. We found that actors faced many challenges and engaged in four interconnected types of knowledge work to address them: exploring, complementing, mapping, and modeling. This article reveals how Hacking Health's open innovation approach used different kinds of temporary spaces to progressively orient actors in their knowledge work to develop sustainable collaborations to create digital health solutions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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