Communities of Innovation at the Ubisoft Montréal’s Studio
Bibliographic record
Abstract
With over 2, 000 employees, Ubisoft Montreal’s studio is the largest video game development office in the world. Established in 1997 by the French-owned multinational group Ubisoft (one of the world’s leading video game developers and publishers), the studio quickly became a creative flagship. It successfully launched many blockbuster games (over 5 million units sold), which became powerful brands for series development on consoles and other platforms (e.g. Prince of Persia, Rainbow Six, Splinter Cell, Assassin’s Creed and Far Cry), and developed franchised games with strong consumer impact (e.g. Peter Jackson’s King Kong or James Cameron’s Avatar). Like many creative organizations with multiple projects, the studio fits the description of a project-led organization (Hobday, 2000), with a portfolio of approximately 15–20 projects in parallel. The projects are managed through a “classic stage-gating process, ” which implies some very strong sets of creation, conception and production routines very well assimilated by project team members. Each project is independent and the project manager literally acts as a semi-autonomous entrepreneur, under local control of the studio’s president and under the ad hoc and remote control of the marketing and creative department from the headquarters in Paris…
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.008 |
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".