Readability Analysis of Laws Related to Public Financial Responsibility and State Budget: A Comparison of Selected Countries
Bibliographic record
Abstract
Abstract In this study, various acts including regulations of public financial management, fiscal responsibility, and state budget in the selected six countries were subjected to different readability tests, and an international comparison was made. The fiscal responsibility act of six countries – Turkey, the UK, India, Australia, Canada, and Pakistan – were included in the study and analyzed. Each country was analyzed under its official language. Since English is an official language of all of the countries except for Turkey, the authors have evaluated the fiscal responsibility acts of these countries using the following readability tests: Flesch Reading Ease, Flesch-Kincaid, Gunning-Fog, and Dale-Chall. Additionally, Public Financial Management and Control Law No. 5018 approved in Turkey was analyzed by the Ateşman Readability Test which was uniquely designed for Turkish grammar rules. The acts discussed in the study were analyzed not only as a whole but also in parts and subsections. According to the results of the study, the levels of readability of the existing laws in most of the selected countries are very difficult to understand for a university graduate. However, when the readability level of the British Budget Responsibility and National Audit Act tested as parts and subsections and a whole, it was rated at a level a university student could understand. This study analyses the readability and intelligibility of acts related to fiscal responsibility and the state budget in six selected countries, adopting Anglo-Saxon public administration model and making an inter-country evaluation. Since it is important that citizens have enough information about legislation for a citizen-oriented understanding, a legislation system that is understood by the larger part of the society is essential.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".