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Record W2474981787 · doi:10.15863/tas.2016.06.38.5

THE STANDARD OF LIVING OF THE POPULATION IN THE RUSSIAN FEDERATION AND ITS SOME GENERAL THEORETICAL ASPECTS OF THE STUDY FOR THE 1ST QUARTER OF 2016

2016· article· en· W2474981787 on OpenAlexaboutno aff
Альмир Анфирович Миниахметов, Albina Faritovna Malikhova

Bibliographic record

VenueTheoretical & Applied Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsRussian federationQuarter (Canadian coin)Standard of livingPopulationPolitical scienceRegional scienceGeographyDemographySociologyLaw

Abstract

fetched live from OpenAlex

The article deals with general theoretical approaches for determining the statistical characteristics of the level and quality of life in the Russian Federation for the 1st quarter of 2016. There are given factors significantly affecting the quality and standards of living of its citizens. Here is offered some quality of life assessment for all regions of the country and are analyzed statistical standards of living represented by the Federal State Statistics Service of the Russian Federation until March 2016. The article has the examples of the main components of standards of living for the two groups of citizens. Income differentiation is showed as a recommendation of one of the methods of characteristics of the standards of living. The index of income concentration for the 1st quarter of 2016 was calculated and was made a comparison with 2015.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.285
Teacher spread0.273 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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