Az agrárium versenyképessége az Európai Unióban: fókuszban a tejipar
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The European Union produces 15% of its agricultural production in the dairy industry. Furthermore, one quarter of global milk production is produced in this region, and European milk consumption is three times higher than the world average. In 2017, total milk production for the EU28 was 170.1 million tonnes, the vast majority of which is cows’ milk production, 164.8 million tonnes. Consumption of fresh dairy products in EU Member States totalled 30.7 million tonnes of milk and 15.6 million tonnes of other fresh dairy products (Eurostat, 2017). The article focuses on the European Union’s and Hungary’s dairy export and analyses it with Balassa’s (Revealed Comparative Advantage, RCA) index. Our aim is to explore the foundations of the region’s competitiveness and the role and opportunities of Hungarian dairy sector. The analysis is based on EU dairy export data for the period 2000–2017. The main result of the analysis is that in terms of competitiveness, the order of the countries, export performance (the largest ones: Denmark, France, Ireland and Belgium) is not fully in line with the order of dairy producing and processing (the largest ones: Germany, France, the United Kingdom, the Netherlands) or dairy export (the largest exporters: Germany, Netherlands, France and Belgium). The reason is that the highest customer value can be achieved through the production of high-end products, and the most competitive countries specialise in the production of one or a few of these products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.053 |
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 it