The Pension Funds’ Investment Regulation at the Beginning of the 21st Century: Comparative Analysis of Approaches of the USA, Canada, and the EU-15 Countries
Bibliographic record
Abstract
The article considers the main trends in the EU-15 countries, the USA, and Canada with regard to the current approaches to the pension funds’ investment activities regulation. This countries’ choice is caused by the relevant static information availability, as well as by the private pension funds’ growing role in this group and the diversity of the investment activity funds forms. The difference between the growth rate of the average pension funds and the GDP in a certain country has the special attention because the leading indicators of the funds volume growth, attracted by the pension systems compared with the economy growth as a whole, determine the possibility of higher payments to pensioners and also allows to increase the pension plans coverage of other population groups. The article deals with the legal aspects of the pension funds regulation with respect to their investment strategies, and contains a comparative analysis between the countries. DOI: 10.5901/mjss.2015.v6n4s4p155
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".