MétaCan
Menu
Back to cohort
Record W2982367518 · doi:10.5430/ijhe.v8n7p146

Educating the Reputation Capital Impact of a Region on the Parameters of Its Investment Activity: Methodical Approaches

2019· article· en· W2982367518 on OpenAlexvenueno aff
Марат Рашитович Сафиуллин, Alexander Stanislavoich Grunichev, Leonid Alekseevich Elshin

Bibliographic record

VenueInternational Journal of Higher Education · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Identity and Reputation
Canadian institutionsnot available
FundersKazan Federal UniversityRussian Foundation for Basic Research
KeywordsReputationInvestment (military)Capital (architecture)Set (abstract data type)Space (punctuation)State (computer science)Human capitalEconomic growthPolitical scienceEconomicsPublic economicsEconomic systemSociologySocial scienceGeography

Abstract

fetched live from OpenAlex

As a practice and empirical observations show, the educational activity of economic agents forms a whole set of prospects for their development. It is due to stable positive or, on the contrary, negative expectations of prospective counterparts that interact with the economic agents, of the possibilities of their development in both the conjuncture and the institutional directions. In this regard, education is very important, and its study is becoming widespread in the research field. Meanwhile, it should be noted that the studies of the question posed in the space of scientific work and research mainly concentrate on the micro-level. That is, the vast majority of works are devoted to the study of the education of firms as one of the most important "representatives" of economic agents. At the same time, the study of educational capital and its influence on the development of regional / national economic systems is unfairly deprived of attention. It is necessary to state that in recent years, the attention of scientists began to focus more and more on the issues set earlier. However, the theory of the territories' educational economy has not yet received development and attention. This largely restrains the research paradigm based on the study of intangible factors of production in the system of socio-economic development of regions or national economic systems in general.In this regard, and to level this gap, the time course of the reputation capital index for the Republic of Tatarstan and the main components determining its level are built in this paper based on the developed methodological approaches to a formalized assessment of the reputation of a territory. This allowed us to assess the reputation impact on the investment activity of a region using the methods of econometric modelling. In particular, being guided by the principles and tools of regression analysis, as well as relying on the method of dummy variables, a high level of interconnection between the studied parameters was established by the authors due to the significant level of elasticity between the analyzed series found.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.220

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 communication0.0000.001
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 head0.075
GPT teacher head0.321
Teacher spread0.246 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Higher EducationSame topicCorporate Identity and ReputationFrench-language works237,207