Productivity among firms patenting in fourth industrial revolution technologies
Bibliographic record
Abstract
This study analyses the links between patenting activity in technologies related to the Fourth Industrial Revolution (4IR) and firms’ performance, as measured by labour productivity, multi-factor productivity, value added and employment, with a focus on companies operating in Canada. The paper provides a descriptive analysis of global patenting activity in 4IR technologies, comparing Canada vis à vis other countries. Canadian resident applicants have significantly developed innovations in 4IR technologies, but at a slower pace compared to global trends. Canadian resident innovations tend to be more original and radical. Econometric analysis is conducted using confidential firm-level data from Statistics Canada alongside matched patent-to-company data from ORBIS©. The results show that firms filing 4IR patents are larger and more productive on average. In the Canadian dataset, as firms develop new 4IR patents, they increase their relative productivity, while in both the Canada and ORBIS© samples, they increase their employment and value added relative to other firms.
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How this classification was reachedexpand
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".