Bibliographic record
Abstract
The topic of the thesis are issues related to the government debt financing. Nowadays, the issue of the state debt is becoming more and more topical, especially as a result of the hundreds of billions of Czech budget deficits. Moreover, it is an area that affects directly or indirectly every person in the Czechia. It is therefore desirable to address the subject thoroughly, because it is an issue that has a multi-generational dimension and the consequences of today's budget negotiations may cause very unpleasant consequences for future generations. Although the level of Czech debt is relatively low compared with the countries of the European Union, in the fourth quarter of 2022, the Czech Republic became, by a wide margin, the fastest-debting country in the European Union. The thesis is divided into three parts.The first part introduces the reader to the issues and describes the key mechanisms of the functioning of the state budget.It describes what the national debt is, what its causes are and why the national debt has been growing steadily by orders of magnitude higher in recent years than it has been in the past decade. Mandatory and quasi-mandatory expenditures are identified as a major problem for public finances in the Czechia and is given special attention, including a model example that highlights...
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".