Bibliographic record
Abstract
Entrepreneurship is a process which proceeds in stages and is characterized by variableintensity. That is why we need methods and measurement instruments that help us to follow itsimage with precision and in particular stages. According the studies conducted by GlobalEntrepreneurship Monitor, two groups of people who are involved in a new economic enterpri-se, can be identified. The first group consists beginning entrepreneurs, active in developing oftheir companies run for 34 years. People from the second group are trying to start their busi-ness and independently or together with their partners undertake some definite activities (suchas looking for location of the company, working out the strategy of their activity, looking forfunds and business partners).Basal measurement or so called coefficient of entrepreneurship (the engagement rate in a neweconomic enterprise) reckons sum of two indexes for two groups. In 2004 the entrepreneurshipcoefficient in Poland amounted 8,3%. It means that among thousand Poles at the age of 1864,almost 90 are involved in starting or developing their business. The value of this coefficient hasincreased to 1,6% in comparison with the previous 2000/2001 years. The value of this entrepre-neurship coefficient in Poland is high and is higher than similar one in Ireland, Norway, Israel,Great Britain, France, and Greece. Only such countries as Canada, Argentina, Australia and Brazil have higher value of the coefficient. Comparing the value of analyzed coefficient amongthe countries of European Union, only Ireland gets ahead Poland and at the same time therewasnt statistically essential difference between coefficient of value in Poland and Ireland.Among countries in political system transformation, except Poland, only Hungary had a highcoefficient of value, however Croatia, Slovenia and Russia accepted the lowest value amongEuropean countries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".