An Assessment of the Impact of Legal Regulation on Financial Security in OECD Countries
Bibliographic record
Abstract
The recurrent economic and financial crises expose the state, enterprises, and households to a range of financial risks and negative financial consequences. As a result, governments are seeking the most efficient measures of legal regulation and other measures ensuring financial security in order to address financial insecurity. The financial security can be considered from a variety of perspectives, and this research proposes that microeconomic and macroeconomic indicators be taken into account when assessing the financial security situation. The results of this research confirmed that legal regulation has a significant positive impact on financial security in OECD countries during the analysis period. Based on the results of the study, it can be argued that legal regulation, including anti-corruption measures, must be an essential part of the financial security strategies being developed. The studies carried out provide a platform for further research, which will allow identification of regulatory measures that would most effectively contribute to financial security needs in individual OECD countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".