'Innovation policy is a team sport' - insights from non-governmental intermediaries in Canadian innovation ecosystem
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
Policy-makers and practitioners alike have increasingly embraced the innovation ecosystem approach to support the flow of knowledge within the Triple Helix framework. This approach focuses on the collaborative and interdependent nature of innovation, which is based on social aspects of knowledge transfer supporting relationships, partnerships, and connections. The important role of intermediary stakeholders that help to facilitate such partnerships is under-researched. This paper examines the work of three intermediary stakeholders in the Canadian innovation ecosystem-the Canadian Science Policy Centre, the MaRS Discovery District, and university Vice Presidents Research. By interviewing 40 experts from the federal and provincial governments, non-governmental organizations, industry, and the higher education sector in Ontario, this study examines how innovation ecosystems are created and what factors influence the success of bringing diverse stakeholders together. The findings suggest that strong political vision and leadership, an inclusive approach to recognizing the needs of diverse stakeholders, and clarity on ways to measure and fund innovation serve as important factors in the Canadian innovation 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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