CONTRIBUTION OF FOOD PRODUCTION SECTOR TO THE INCREASE OF EMPLOYMENT – COMPARATIVE ANALYSIS OF SLOVENIA, CROATIA, AND SERBIA
Bibliographic record
Abstract
The processing sector in Serbia has not managed to consolidate even after more than a quarter century since the breakup of the former Yugoslavia. Food production in Serbia shares the fate of the entire production sector, as its integral part. Despite this fact, food production is more and more seen as the opportunity for increasing employment and the level of economic activity in Serbia. Especially after the introduction of EU sanctions by Russia, advocates of export of food products as the development opportunities for Serbia are growing louder. This made us pose the research question relating to whether economic growth in the area of food production has effects on employment level in Serbia? In searching for the answer to this question, we constructed a sample of the 20 largest food producers in Serbia and investigated the correlation between the level of economic activity in these companies and the number of their employees. We did the same for the 20 largest manufacturers in Slovenia and Croatia, and tested the hypothesis about the food production as the development opportunity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".