State budget system improvement for informed decision-making in Latvia
Bibliographic record
Abstract
The study aims to improved the state budget system to ensure informed decision-making, which will contribute to more efficient use of budget funds and increase national financial stability. A comparative analysis of successful budget planning practices in other countries, such as Sweden, Canada and Estonia, was conducted, and the legal framework for coordination between government agencies in the budget management process in Latvia was reviewed. The methodological approach was based on the analysis of statistical data from official sources and regulations, as well as the use of information from government and ministerial websites. The results of the study showed that the analysis of revenues and expenditures of the Latvian state budget for the period from 2019 to August 2024 revealed a steady increase in revenues, with the exception of a decline in 2020 due to the pandemic, and an increase in expenditures, which requires optimisation and better coordination between government agencies. The study determined that the existing legal framework of Latvia regulating coordination between state institutions in budget management needs to be improved to increase the efficiency of this interaction. A comparison of Latvia's budget management systems with the successful practices of Sweden, Canada and Estonia demonstrated management improvement potential by introducing long-term strategic planning, as in Sweden, integrating results into the budget process, as in Canada, and increasing transparency and public involvement, as in Estonia. Based on the data obtained, recommendations were developed to integrate new technologies into the budget process and increase transparency, contributing to a more efficient use of public resources. The results indicate the need to reform the state budget system to ensure informed decision-making in Latvia. This will make it possible to use budget funds more rationally, increase the transparency of financial processes and strengthen public confidence in government decisions
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.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".