Bibliographic record
Abstract
In this monograph, we analysed all companies and entrepreneurs in Slovenia for the year 2017, then we compared for the year 2016 or 2015 key data of Slovenia and EU-28 or individual member states in the non-financial business economy. In Slovenia, in 2017 122,618 businesses employed 563,356 people. The majority of businesses (nearly one fifth) operated in the wholesale and retail trade; maintenance and repair of motor vehicles. Likewise, in the EU-28 in 2016 more than a quarter of businesses (25.9% or 6.3 million) was active in the wholesale and retail trade; maintenance and repair of motor vehicles. The average value added per person employed for the aggregated activities of the EU-28 in the year 2016 amounted to 50,900 euros, while in Slovenia 32,700 euros (36% less). In the second part, we studied the transfer of companies. We surveyed a selected sample of experts who represent important actors in a supportive environment for SME transfers. We also carried out a survey on the transfer of companies among the founders/owners of SMEs in Slovenia. We were interested in what type of support they need in this process. In this, we limited ourselves to the age group of entrepreneurs 55+.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| 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) | 0.007 | 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".