Science and Business Cooperation. Barriers in Poland Within the Context of Selected European and North American Countries
Bibliographic record
Abstract
This article focuses on the theoretical and empirical analysis of factors affecting the cooperation between science and business. The author will present the results of empirical research conducted in Poland, the Czech Republic, Hungary, France, Norway, the United States of America and Canada. The analysis will indicate how and which factors: structural, systemic, competence or awareness and cultural can be utilised in the commercialisation of knowledge and technologies. The analysis of research outcomes which underpins this study is also set on the following assumptions: \n \nEvery country has different barriers to cooperation between scientists and entrepreneurs; \nPolish scientists and entrepreneurs should rely on proven and significant factors conducive to cooperation between science and business in Poland; \nAcademic centres in Poland can benefit from the experience gained by other countries to intensify its model of cooperation with entrepreneurs. \nThe article will showcase the research results that relate to the identification of selected problems occurring in establishing and maintaining cooperation between Polish scientific research organisations and entrepreneurs in the context of selected countries whose respondents were subject to empirical research.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".