MANAGING THE CO-CREATION PROCESS: WHEN THE CAKE DOES NOT RISE
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
Co-creation is recognised in the literature as fostering successful collaboration between academia and industry. Although models do exist, they only contain general principals and provide no details about the process from ideation to value creation. Moreover, they are established based on a consideration that industry submits a problem and the university provides solutions. However, with increasing pressure on researchers for their research to lead to tangible applications, universities must now also turn to firms to pinpoint their needs and practices. The purpose of this paper is to understand how a researcher can implement and manage a co-creation project in collaboration with firms to foster innovation. A university research team in food science and technology, in response to the issue of allergen management in the food service industry, more specifically the use of eggs in pastries, has led a co-creation project with six professional pastry chefs to improve cake formulations, in which eggs were replaced with legume puree. Based on the results and the literature, a model to manage the co-creation process between academia and industry that incorporates a collaboration platform is proposed. This paper also identifies the concrete practices that foster creativity and interaction among participants and that lead to innovation.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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