Information Technology at Cirque du Soleil: Looking Back, Moving Forward
Bibliographic record
Abstract
What do information technologies (IT) have to do with running an artistic organization such as Cirque du Soleil? It turns out that they are critical to the success of the organization. The case is situated in 2008 when Cirque had developed an IT infrastructure supporting the entire process value chain from show creation to production and design, casting, and logistics needed for running its 17 shows around the world. The case illustrates how IT can support different processes of firms, even those relatively ill-structured and which rely heavily on creativity. It also generates discussions on the notion of IT strategic alignment and brings students to reflect on the challenges associated with sustaining alignment over time.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".