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Record W2004335921 · doi:10.5539/ass.v10n13p271

Reputation as Part of Intangible Property, Intangible National Wealth and Intangible Heritage

2014· article· en· W2004335921 on OpenAlexvenueno aff
Julia Kolesnikova, А.С. Груничев, E.F. Salyahov, V. M. Zagidullina

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Regional Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsIntangible propertyIntangible goodReputationIntangible assetBusinessCapital (architecture)Business operationsProperty (philosophy)CommerceIndustrial organizationMarketingEconomicsProperty rightsAccountingEconomyMicroeconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

The role of intangible values increases in the modern information society: knowledge, information, reputation and other intangible objects are capable to provide a competitive advantage of individual companies and states in general. The share of intangible capital in the structure of national wealth of the majority of developed countries increases. In our opinion, in the modern economic science there are no accurate criteria differentiating such categories as intangible heritage, intangible national wealth and intangible property that leads to the mix of concepts and complicates the definition of mechanisms which increase the intangible capital at the state level. One of the objectives of our research is differentiation of categories of intangible national wealth, intangible property, intangible heritage and identification of intangible objects, which they include. A large number of modern researches are devoted to the topic of reputation, scientists agree that this intangible resource has a great impact on competitiveness and efficiency of economic activity. However reputation isn't considered on a macrolevel, its influence on the activities of regions or country is not studied, questions of studying of the essence of reputation and factors influencing it at the macrolevel became the second problem of our research. The objective of this research is the study of reputation as a part of intangible wealth, heritage and property and identification of the factors which can be considered as a source of the increase in these intangible assets. Statement and proof of working hypotheses were carried out on the basis of methods of classification, analysis, synthesis, standardized analytical approach and analogy. As a result the reputation is considered to be the phenomenon with multiple aspects, which is subject to numerous factors such as actions and events in the region, social, economic, political and legal status of the region and etc. The analysis of reputation of the Republic of Tatarstan is carried out. It is defined that the improvement of reputation of the country and region increases the intangible national wealth, intangible property and intangible heritage.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.247
Teacher spread0.219 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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