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Record W3153730020 · doi:10.21272/mmi.2021.1-26

Innovation development and migration: panel data approach

2021· article· en· W3153730020 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMarketing and Management of Innovations · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicBusiness and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsScopusGovernment (linguistics)Corporate governanceIntellectual capitalPanel dataPolitical scienceLanguage changeAccountabilityIndex (typography)Human capitalBusinessEconomic growthEconomics

Abstract

fetched live from OpenAlex

The intellectual capital is a catalysator of the country’s economic growth. The developed countries try to develop attractive conditions for highly qualified migrants to diffuse the knowledge and innovations. The authors provided the bibliometric analysis of the papers, which focused on the analysis of the migrant issues was done. For the bibliometric analysis, the metadata of 2 500 papers was selected from Scopus. The results showed that the numbers of Scopus documents on the allocated theme have increased for 2015 year. The most powerful investigations were provided by scientists from the USA, Canada, France, United Kingdom. The bibliometric analysis findings confirmed that the scientists allocated a vast range of the determinants that could stimulate or restrict the migrants in the country. Thus, the governance efficiency had the mediation role between the migration and innovation development of the country. In this case, the paper aims to check the hypothesis that the increasing (decreasing) level of country innovation development and government efficiency from year t − 1 to year t positively (negatively) affects net migration in year t + 1. The panel data for 2011-2018 was generated from IndexMundi, EU Data Portal, WorldBank. The object of the investigation was Bulgaria, Croatia, Lithuania, Latvia, Poland, Romania. The dependent variables – net migration rate, the independent variables – World Government Indicators: Control of Corruption, Government Effectiveness, Political Stability, Rule of Law, Regulatory Quality, Voice and Accountability (for assessment of government efficiency), Innovation Index (for assessment of country's innovation development). In the paper, to check the hypothesis, the authors used the Fully Modified Ordinary Least Square for homogeneous and heterogeneous models. The findings confirmed that innovation development and governance efficiency (Political Stability and Absence of Violence/Terrorism, Regulatory Quality, Voice and Accountability) had a statistically significant impact on the migration rate. The findings could be used to identify the strategic goals of innovation development to overcome the demographic issues and support the migration of the high qualified workforces.

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.

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 score0.838
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.057
GPT teacher head0.230
Teacher spread0.173 · 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