Index of protection of the interests of consumers of the financial services market
Bibliographic record
Abstract
The world practice shows that active activity of international organizations in the direction of improving the system of protection of the rights of consumers of financial services gives first positive results after the crisis of 2008-2009.However, the theoretical basis, declared by international organizations, does not always coincide with the actual state of events in countries with different levels of economic and social development.This problem requires a more complex solution with the use of more flexible tools.In this article, key regulatory provisions were analyzed, which are currently regulating the process of providing the system for protecting the rights of consumers of financial services.Based on world experience, it is suggested to use the so-called index of the safity of customers of the finacial services market (ISCF), which is calculated on the basis of variables, united by three structural units: financial literacy, financial consumer protection, financial inclusion, to assess the degree of customer protection.This index was calculated for 142 countries with different levels of economic development.According to the results, the highest value of the index was found in the countries with developed economies (Belgium, Great Britain, Canada, Portugal and France).It confirms that the level of the economic development correlates with ISCF and there is direct connection.So, as country is more economic developed it has higher ISCF.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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) | 0.005 | 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".