DEVELOPING INDICATORS OF OPEN INNOVATION EVENT OUTCOMES
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
Open innovation (OI) events are potent instruments for the development of dynamic ecosystems. However, the literature analyses the structure and mechanisms of OI events insufficiently to demonstrate their efficacy, making it difficult to justify the investments necessary for their success. With better data confirming their impact, funding for OI events should improve by becoming more accessible and, therefore, more conducive to efficient value creation. This regional study contributes to the literature on innovation ecosystems and field-configuring events by responding to the call for more effective measures of OI events to coordinate and improve the ecosystems’ overall competitiveness. Based on an analysis of six in-depth case studies, 28 semi-structured interviews, and secondary sources, we identify 54 best practices and 34 indicators of an event’s success for various actor types. Moreover, we suggest 11 measures of the short- and long-term impacts of an event on its ecosystem.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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