Przedsiębiorczość akademicka. Dobre praktyki
Bibliographic record
Abstract
Polish Abstract: Niniejsza publikacja jest zbiorem „dobrych praktyk" przedsiębiorczości akademickiej zidentyfi kowanych nie tylko w Polsce ale także w Stanach Zjednoczonych, Niemczech, Chinach, Szwajcarii, Belgii, Włoszech, Szwecji, Kanadadzie i Wielkiej Brytanii. Praktyki pochodzą z różnych sektorów gospodarki takich jak: biotechnologia, medycyna, farmacja, biofarmacja, elektronika i automatyka, półprzewodniki, nanotechnologia, elektronika, elektromechanika, analiza środowiskowa, informatyka, internet, multimedia i komunikacja. Wskazano także przykłady „przedsiębiorczych uniwersytetów", w przypadku których mamy do czynienia z świadomym nastawieniem całych społeczności akademickich na rozwój przedsiębiorczości w wielu sektorach gospodarczych jako podstawy własnej strategii rozwoju. Choć zaprezentowane przykłady mogą się wydawać odległe, to łączy je umiejętność przekuwania wiedzy generowanej w sferze nauki na sukcesy ekonomiczne. Korzyści osiągają nie tylko bezpośredni przedsiębiorcy akademiccy, ale także innowacyjne przedsiębiorstwa, regiony czy kraje oraz same uczelnie. English Abstract: This publication is a collection of "good practices" of academic entrepreneurship identified not only in Poland, but also in the United States, Germany, China, Switzerland, Belgium, Italy, Sweden, Canada and the UK .. The practices come from various sectors of the economy such as: biotechnology, medicine, pharmacy, biopharmaceutics, electronics and automation, semiconductors, nanotechnology, electronics, electromechanics, environmental analysis, IT, internet, multimedia and communication. Examples of "enterprising universities" are also indicated, where we are dealing with the conscious attitude of entire academic communities at development of entrepreneurship in many economic sectors as the basis of own development strategy. Although the presented examples may seem distant, they are connected by the ability to translate knowledge generated in the sphere of science into economic successes. Not only direct academia benefits, but also innovative enterprises, regions or countries and universities themselves.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.007 |
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".