Slovenian Companies and Characteristics of Start-up Ecosystem: Slovenian Entrepreneurship Observatory 2015
Bibliographic record
Abstract
In this monograph, we first analysed all companies and entrepreneurs in Slovenia in 2014; then, for 2012, we compared the critical data for companies from the EU-28 and Slovenia in the non-financial business sector (activities of industry, trade and services). In Slovenia in 2014, 63,590 companies (almost 4% more than in the previous year) and 67,500 entrepreneurs (3% less than the previous year) − totalling 131,090 enterprises − employed more than 526,000 people. More than one quarter of enterprises in the non-financial business sector in the EU-28 in 2012 operated in distributive trades (motor trades, wholesale trade and retail trade). This activity also employed the most people (i.e., one quarter). In order to learn more about Slovenian start-up companies, the start-up ecosystem and the key challenges for improvements, we analysed the characteristics of Slovenian start-up companies and the start-up ecosystem. We employed primary data from 156 start-up companies, whose average age was 2.1 years, included in the research study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".