The importance of EU support program to the Western Balkans: The example of the Republic of Serbia
Bibliographic record
Abstract
In its overall policy the European Union is fully focused on the regional cooperation program and development of the Western Balkans, particularly regarding the EU enlargement policy. These countries have access to EU capacities through numerous financial support programs and technical assistance to enable the economic development and prosperity of the countries, their political stability and security. The aim of the paper is to show how these support programs to the institutions and organizations contribute to the development of the Republic of Serbia in the regional development and cooperation in the Western Balkans. To resolve the issues of mutual concern regarding unfavorable economic situation in most countries of the Western Balkans, financial support is vital what is exactly the purpose and aim of the EU support programs. Through the regional support programs, as well as the incentives to the countries to improve their regional cooperation, EU simplifies the access to loans. It is conducted by uniting and coordinating different sources of funding and technical assistance. Moreover, it provides the support to the administration and implementation of the CBC program. In this way the institutional and organizational capacities, regional and social infrastructure, as well as regional initiatives between the countries of the Western Balkans are improved.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".