Актуарно-статистические условия регулирования пенсионного возраста в Российской Федерации
Bibliographic record
Abstract
The problem of rising the retirement age in our country has been under discussion since the outset of market reforms of pension systems (i. e. a quarter of a century), and it still has no apparent progress towards a solution. In anticipation of the predicted in the middle of the last century demographic crisis, most civilized countries have embarked on a radical overhaul of not only their social sphere (development of social services, «accessible environment» for people with disabilities, orientation of health care system on gerontological problems, etc.), but also in terms of macroeconomic reallocation of resources according to growing needs of current consumption and maintenance of disabled citizens. The main emphasis is placed on the direct economic stimulation of birth rate. The latter contributed significantly to the leveling of the negative «demographic gaps». However, the whole complex of problems of aging population goes far beyond a simple reproduction of the population. In the current socio-economic conditions, the problem of rising the retirement age in Russia has become particularly acute. The practice of Western countries shows that only when favorable macro-economic and social conditions are created, a positive effect is reached with regards to implementation of institutional and parametric reforms of a pension system in terms of raising the retirement age and the implantation of funded mandatory pension schemes for employers.. This article is the first to present actuarial analysis of demographic, social and labor conditions and prerequisites for rising the retirement age in Russia, which was conducted using official statistics.
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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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.021 |
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".