Mapping Regional and Sectoral Characteristics of Knowledge‐Intensive Business Services: Evidence from the Province of Quebec (Canada)
Bibliographic record
Abstract
ABSTRACT The study presents original evidence on the characteristic features and innovation activities of knowledge‐intensive business services (KIBS). Based on a wide‐scale survey of 1,124 KIBS firms in Quebec (Canada), we explore empirically the extent to which KIBS from various sectors and regions differ in their characteristics and their uses of innovation practices. The results from the sectoral analysis reveal that KIBS display different characteristic features and innovation behaviours across sectors, thus suggesting that inter‐sectoral differences are important when explaining innovation activities in KIBS. The comparison between KIBS in large, medium, central, and resource regions shows that the characteristic features and the innovativeness of KIBS are rather similar, and little or no significant statistical differences were found between the different regions in the province of Quebec. Thus, overall, the results of our study seem to suggest that a location does not tend to make a difference in respect to characteristic features and innovation performance of KIBS.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".