.Research Policy 28 1999 215–230 Canadian R&D abroad management practices
Bibliographic record
Abstract
In the 1980s, Canadian industrial R&D abroad has grown substantially. In 1995, R&D expenditures by Canadian affiliates, only in the United States, represented some US$1.4 billion and employed some 6300 persons. Nearly 60 Canadian-owned and-controlled corporations conduct overseas R&D, mostly in the US, Western Europe, Japan, and Australia. Canadian corporations are performing commercial R&D abroad in order to support their manufacturing subsidiaries and to come closer to customers and markets. A secondary motivation is to hire skilled personnel, monitor foreign technological development and increase the inflow of new ideas into the corporation. They also chose friendly socio-political environments from a regulatory point of view. Technology transfer and adaptation to local markets is also an important mission of the foreign R&D establishment. Foreign R&D activities of Canadian firms are fairly decentralized and autonomous. Most of the foreign subsidiaries undertook R&D abroad before they were acquired by the Canadian corporation; also the number of Canadian managers was reduced and the R&D projects were usually decided in the affiliate. Three main types of expatriate R&D were found: a majority of the subsidiaries were producing goods in the same or related .industries as in Canada such as machines, transportation equipment or housing equipment. A second group of firms were vertically integrated firms, that conducted process research in Canada and advanced materials and final products research abroad, closer to the markets for this type of goods; they were active in the chemical and metal industries. Only one truly
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.100 | 0.015 |
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".