Capacités d'innovation: utilisation de technologies, croissance de la productivité et rendement des entreprises: résultats des enquêtes canadiennes sur la technologie
Bibliographic record
Abstract
Le présent document résume les résultats de plusieurs études de recherche menées par la Division de l'analyse microéconomique de Statistique Canada qui portent sur les répercussions de l'utilisation de technologies de pointe sur le rendement des entreprises. Ces études s'appuient à la fois sur des données d'enquête au niveau de l'établissement sur les pratiques liées aux technologies de pointe et sur des données longitudinales qui mesurent les variations du rendement relatif. Ensemble, ces études fournissent des preuves convaincantes que les stratégies d'utilisation de technologies ont une incidence considérable sur les résultats sur le plan de la concurrence, après prise en compte d'autres corrélats du rendement des établissements. Il y a lieu de mettre l'accent plus particulièrement sur les technologies de communication de pointe, puisque leur utilisation est étroitement associée à la variation de la productivité relative.
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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 | 0.016 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".