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Record W4384300870 · doi:10.6000/1929-7092.2023.12.02

Selected Aspects of Internationalization in the Liberec Region and the Free State of Saxony

2023· article· en· W4384300870 on OpenAlexvenueno aff
Zuzana Potužáková, Jaroslav Demel

Bibliographic record

VenueJournal of Reviews on Global Economics · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
FundersInterregEuropean Regional Development Fund
KeywordsAccessionInternationalizationPosition (finance)Political scienceGeographyEuropean unionInternational tradeEconomyEconomic geographyBusinessEconomics

Abstract

fetched live from OpenAlex

Internationalization is a widely discussed topic analysed from various points of view. In our paper, we have decided to measure this trend in two border regions in former Eastern Germany and in Czechia, namely in Saxony and the Liberec region in the time period 2013-2020. Both areas belonged to the Eastern bloc before 1990. Saxony experienced a rapid reunification process within the early 1990s and Czechia a transformation process competed in 2004 by the EU accession. In our paper, we have decided to test three hypotheses. First, we tested if Saxony is more internationalized in terms of human resources (1) and secondly with regard to export output (2). Then, we conducted the same tests on the Liberec region. Our assumption was that, due to the rapid reunification and favourable geographic proximity of lucrative Western markets, the position of Saxony would be more advanced. Finally, we tested the hypothesis (3) that the rising number of foreign workers contribute to the rising export volumes. We correlated the indicators of employed foreigners and exports per head in both regions from 2013 to 2020.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.242
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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