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Record W1996359607 · doi:10.5539/ass.v11n7p74

Socio-Economic Potential of the Region and Its Evaluation

2015· article· en· W1996359607 on OpenAlexvenueno aff
Valeria A. Cheymetova, Elena Victorovna Nazmutdinova

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigitalization and Economic Development in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsProsperitySocioeconomic developmentManagement scienceEconomic systemEconomicsEconomic growth

Abstract

fetched live from OpenAlex

At the moment the problem of determining the internal reserves of socio-economic development of the regionbecomes more important, the solution of which requires the development of new approaches to the definition ofthe essence, structure, methods for assessing the socio-economic potential.Modern socio-economic situation and the need for constant adjustment of the processes occurring in the regionrequire the development and formation of the conceptual and methodological tools of complex analysis of thelevel of development potential of the area. Now there are several basic approaches: integral evaluation ofmeasures of socio-economic prosperity of the regions; integrated comprehensive performance evaluation basedon the additive and multiplicative criterion.One of the policy objectives of socio-economic development is the establishment of long-term regionaldevelopment priorities. Comprehensive assessment of the dynamics of development of the Russian Federationsuggests some stabilization of the socio-economic situation in them. However, some regions are significantlybehind in terms of its socio-economic development. Therefore strategically important for Russia is a coherentstate regional policy.The aim of this study is the development of theoretical approaches, methodological principles, as well as thedevelopment of practical recommendations for a comprehensive assessment of the socio-economic potential ofthe region.During the study of the theoretical framework for assessing the socio-economic potential of the technique in thebalance of social and economic trends on the basis of the calculation of integral indices reflecting the substantialcharacteristics of the local units were constructed indicators (normalized values) underlying the integralevaluation of the balanced socio-economic potential of the region. The application of this approach allows toselect the subjects of the Russian Federation, whose rating is the same when using the resource and effectiveapproaches that demonstrates the effectiveness of management of socio-economic potential of territorial entities.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.238
Teacher spread0.208 · 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 designObservational
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

Citations14
Published2015
Admission routes1
Has abstractyes

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