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Record W2586080167 · doi:10.5539/ibr.v10n3p80

Impact on Economic Growth of Technological Progress in the Turkey Economy: Empirical Analysis on Political and Financial Stability Channel

2017· article· en· W2586080167 on OpenAlexvenueno aff
Nazan Yelkikalan, Erdal Aydın, Ünzüle KURT

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Technological changeEconomicsPoliticsCausality (physics)TurkishGranger causalityEconomic stabilityFinancial stabilityChannel (broadcasting)Economic systemStability (learning theory)Turkish economyMacroeconomicsFinancial systemEconometricsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

As an important dynamic of economic growth in the literature, technological progress is addressed in the study in the context of political and financial stability channels. In this context, the aim of the study is to determine the relationship between effects of technological progress on economic growth and political and financial stability concepts. The study for Turkish economy is based on data of 1984-2014 period and technological progress variable is considered as advanced technology export. As a result of the study, the obtained results of causality analysis showed that political and financial stability are important channels in technological progress and economic growth relation.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.137
GPT teacher head0.389
Teacher spread0.252 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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