ASP, The Art and Science of Practice: Academia-Industry Interfacing in Operations Research in Montréal
Bibliographic record
Abstract
This paper reports on the 40-year experience of academia-industry interfacing in the operations research (OR) field in Montréal. We focus on five spin off companies that academic entrepreneurs from the CIRRELT and the GERAD created between 1976 and 2003: INRO Consultants, GIRO, AD OPT, Omega Optimisation/Planora, and ExPretio. The importance of university spin offs for knowledge transfer is well documented in fields such as biology and nanotechnology; however, few papers have studied university spin offs in OR. Yet, OR has an enormous impact on society, and university spin off firms play a key role in the diffusion of research to the world of practitioners. In this paper, we tell the story of five companies created by academics from two world-renowned OR research centers based in Montréal, and we derive lessons about academia-industry interfacing in the OR field. By so doing, we hope to improve our understanding of the creation of fruitful relationships between academics and OR practitioners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.018 | 0.028 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".