The Analysis of Farm Population with Respect to Young Farmers in the European Union
Bibliographic record
Abstract
The position of young farmers in countries of the European Union is different In the EU-28 treated by Farm Structure Census of Agriculture nearly 9 million businesses. Most farms are located in Romania, Italy and Poland on the other hand, at least in Luxembourg, Malta and Estonia. The largest farms in the EU-28 are in Slovakia (119.3 hectares) in the Czech Republic (134.6). On the other hand, the smallest farms are in Malta (1.2 ha), Cyprus (4.9 ha), Greece (5.6 ha), Slovenia (7.5 ha) and Italy (9.0 hectares). Romania (11.0 ha) and Poland (12.3 ha). The aim of the paper is to analyse position of young farmers in the European Union countries. In the average of the 28 member states of the Union, more than half (55%) of the private farmers is over 55 years old. This rate is prominently high in Portugal (73,4%), not much lesser in Bulgaria (70,3%), Italy (68%) and Romania (67,5%). Meanwhile the age consistence of farmers in Austria and Germany is good, where less than quarter of the farmers belong to the mentioned age class. Hungary is in the middle, similarly to the average of the Union, or Malta and Greece.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".