Comparing Organizational Structure and Design in Canadian & Russian Enterprises based in P.R. of China (Specialized in Hi-tech and Nano-technologies)
Bibliographic record
Abstract
Organizational Design of Canadian Enterprises Based in China (CEBC) and Russian Enterprises Based in China (REBC), which specialize on manufacturing nano-tech and hi-tech products, are being compared in this article. Generally, such enterprises are Russian joint ventures possessing significant scientific potential and aggressively penetrating into the areas of nano- and hi-tech. And Canadian enterprises having classical organizational structure and being leaders in the fields of nano- and other hi-tech. After analyzing the literature on classic organizational design, management problems of hi-tech enterprises in People’s Republic of China (PRC), general problems in management of foreign joint ventures in PRC, including some web recourses, the authors had put forward a few hypotheses. H1: Structural design of joint venture specializing in nanoand hi-tech production, is strongly connected with structure design of a university they are typically tied to. H2: Structural design and related to it main management problems of Canadian and Russian joint ventures have commonalities and differences in the ways connected with the American management model (decentralization, authority delegation).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".