Buying and selling research and development services, 1997 to 2002
Bibliographic record
Abstract
Research and development is a crucial activity in the innovation process. Not every firm is in a position to overcome constraints to R&D, such as costs. Those that perform R&D must choose between forming a partnership with other firms, governmental organisations, universities or doing it themselves internally. Others may sell R&D services or buy them. This study provides a statistical portrait of the strategies Canadian companies used in conducting research and development between 1997 and 2002. It is based on data from the Survey of Research and Development in Canadian Industry. During this time period, the majority of R&D spending, around 62%, was of internal origin, that is, it was conducted by the performer. The remaining 38% portion was comprised of two groups: one group representing 24% performed R&D on behalf of another organization, that is, they contracted in. The remaining 14% was conducted by another R&D performer, that is, they contracted out. An estimated 42% of research and development was conducted with no external partnerships. Foreign-controlled firms were much more heavily involved in selling R&D services than their Canadian counterparts. About 22% of all foreign-controlled firms conducted R&D for outside organizations, more than twice the proportion of only 9% of domestic performers. However, Canadian-controlled firms on average spent more on research and development. As a result, the 9% of Canadian-controlled performers allocated 23% of their total R&D spending to selling R&D services, virtually the same proportion as the 25% allocated by foreign-controlled firms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".