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Record W4399383775 · doi:10.24294/jipd.v8i6.3725

Russian MNCS and international investment paradigm (Before COVID-19)

2024· article· en· W4399383775 on OpenAlexaff
Serzhena Tcyrempilova, Can Ertugrul, Mihály Hegedűs, Mohammad Daud Ali, Lóránt Dénes Dávid, Róbert Magda

Bibliographic record

VenueJournal of Infrastructure Policy and Development · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsSavaria (Canada)
Fundersnot available
KeywordsMultinational corporationCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Investment (military)BusinessPolitical scienceVirologyMedicineInfectious disease (medical specialty)PoliticsDiseaseInternal medicine

Abstract

fetched live from OpenAlex

This study examines the relationship between Russian FDI carried out by large MNCs and investment development path (IDP). Although statistical analysis does not establish a significant relationship between outward FDI and GDP, the behavior of Russian outward FDI contradicts traditional models. Two primary factors contribute to this paradox. First, the complex business environment in Russia, characterized by a combination of both improvements and contradictions, has a significant impact on outward FDI behavior. Secondly, the duality of the Russian economy and society plays a decisive role. This segment resembles a high-income country with ample resources, while most face lower income levels, raising concerns about wealth distribution. Historical factors, including Russia’s transition from a state-controlled to a market-oriented economy, contribute to the internationalization of Russian MNCs. Both state-owned enterprises and privatized firms are influenced by the state, although to varying degrees. Government involvement in international business strategies increases the knowledge and experience of Russian MNCs, but also raises concerns about political influence.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.339
Teacher spread0.311 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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