Ensure the Efficient Use of Local Budgets: What is the Root Cause of the Problem?
Bibliographic record
Abstract
In a market economy, everyone, as far as possible, tries to use the available funds efficiently. This is a separate derived individual, family, enterprise, etc. will be affected. However, despite this, life observations and scientific research have shown that this problem becomes more and more complex as it goes from bottom to top. In particular, one of such difficult problems is the issue of effective use of funds within the framework of local budgets. However, in our opinion, there is a certain paradox here. This is due to the fact that countries operating in market relations and in civilized countries of the world (USA, Canada, Germany, Great Britain, France, Austria, Holland, Italy, Japan, South Korea, etc.)).g.) this problem is already successfully resolved. Nobody doubts that the funds allocated from local budgets in these countries are spent efficiently. This is evidenced by the fact that the real situation exists there. But if we talk about the efficiency of spending funds in the accounts of local budgets in Uzbekistan, then, unfortunately, this cannot be said.
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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 | 0.015 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".