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Record W3108892471 · doi:10.5430/ijfr.v11n6p219

Strategic Management System of the Territory as a Factor of Increasing Its Competitiveness Level in Financial Organizations

2020· article· en· W3108892471 on OpenAlexvenueno aff
Andrey Vorobyev, Irina Glebova, Liliya V. Khafizova

Bibliographic record

VenueInternational Journal of Financial Research · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Regional Competitiveness
Canadian institutionsnot available
FundersKazan Federal University
KeywordsBusinessRussian federationPropositionStrategic financial managementStrategic planningStrategic managementIndustrial organizationFactor (programming language)Process managementFinanceAccountingMarketingComputer scienceEconomic policy

Abstract

fetched live from OpenAlex

This paper proposes a methodology for assessing the development level of the strategic management system and the competitiveness level in financial organizations. This methodology served the basis for an analysis of regions and federal cities the Russian Federation. A correlation analysis is also carried out to define the dependence of the constituent entity's competitiveness on the development of the strategic management system that resulted in the proposition of comprehensive solutions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.884
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.151
GPT teacher head0.314
Teacher spread0.163 · 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 teacher head, 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

Citations0
Published2020
Admission routes1
Has abstractyes

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