Understanding Quadruple Helix relationships of university technology commercialisation: a micro-level approach
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
Given recent demands for more co-creational university technology commercialisation processes involving industry and end users, this paper adopts a micro-level approach to explore the challenges faced by universities when managing Quadruple Helix stakeholders within technology commercialisation processes. To explore this research question, a qualitative research methodology which relies upon comparative case analysis was adopted to explore the technology commercialisation process in two universities within a UK region. The findings revealed that university type impacts Quadruple Helix stakeholder salience and engagement and consequently university technology commercialisation activities and processes. This is important as recent European regional policy fails to account for contextual influences when promoting Quadruple Helix stakeholder relationships in co-creational university technology commercialisation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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