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Record W2953136008

Социально-Экономические Последствия Повышения Пенсионного Возраста В Российской Федерации // Social And Economic Consequences Of Increase Of Pension Age In The Russian Federation

2015· article· ru· W2953136008 on OpenAlexaboutno aff
V. Popov Yu.

Bibliographic record

VenueФинансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice · 2015
Typearticle
Languageru
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsPensionRussian federationQuarter (Canadian coin)Shock (circulatory)Social securityPension systemSocial insuranceEconomic policyEconomicsPolitical scienceBusinessDevelopment economicsMarket economyFinanceHistoryMedicine
DOInot available

Abstract

fetched live from OpenAlex

The problem of increase of pension age in our country is discussed already from the first steps of market transformations of provision of pensions, i. e. quarter of the century, and without some visible advancement to its decision. At the same time all civilised countries have already developed the accurate program of actions under its decision, though and with different social and economic consequences: one have raised pension age “shock” tools for one-two year, others have stretched this process for some decades, the third have refused an age regulator the insurance pension rights. In present social and economic conditions the problem of increase of pension age in Russia has got a special sharpness. Проблема повышения пенсионного возраста в нашей стране обсуждается с первых шагов рыночных преобразований пенсионного обеспечения, т. е. четверть века, и без сколько-нибудь видимого продвижения к ее решению. В то же время все цивилизованные страны уже выработали четкую программу действий по ее решению, хотя и с разными социальными и экономическими последствиями: одни повысили пенсионный возраст «шоковыми» инструментами за один-два года, другие растянули этот процесс на несколько десятилетий, третьи отказались от возрастного регулятора страховых пенсионных прав. В нынешних социально-экономических условиях проблема повышения пенсионного возраста в России приобрела особую остроту.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.050
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0500.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0020.006
Scholarly communication0.0010.006
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.348
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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Same venueФинансы: теория и практика/Finance: Theory and Practice // Finance: Theory and PracticeSame topicRegional Socio-Economic Development TrendsFrench-language works237,207