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Record W2994980225 · doi:10.15407/ingedu2019.52.138

Migration of Ukrainians at the pre-industrial stage of social development

2019· article· en· W2994980225 on OpenAlexaboutno aff
Lesia Didkіvska

Bibliographic record

VenueÌstorìâ narodnogo gospodarstva ta ekonomìčnoï dumki Ukraïni · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianEmigrationPopulationSocioeconomic statusGeographyPolitical scienceHuman migrationEconomic growthDevelopment economicsDemographic economicsSociologyDemographyEconomics

Abstract

fetched live from OpenAlex

The subject of the research is the migration history of Ukrainians at the pre-industrial stage of social development. The purpose of the article is the historical and economic analysis of migration trends and the identification of geographical vectors of the first migration flows on Ukrainian lands and the institutional factors and socioeconomic consequences of the spread of migration sentiment among the population during the period. The result of the study is the identification of features of the first migration flows in the Ukrainian territory, the classification of migration according to its causes, the identification of directions of the resettlement of Ukrainians and the consequences of emigration of Ukrainians. It was revealed that the labour migration of Ukrainians was preceded by political migration related to the regular attacks of Tatars and Turks, the fall of Kievan Rus, the loss of national statehood, the colonization of Ukrainian lands by foreign states. In spite of a number of negative consequences, the Ukrainian people received both economic benefits and qualitative progress in state-building. At the same time, labour migration led to the irreversible loss of the economically active working population, above all the peasantry, who were the most important group among Ukrainian emigrants. The main factors contributing to the labour migration of Ukrainians were similar: institutional (abolition of serfdom), demographic (reduction of mortality rate, while maintaining high fertility), socio-economic (low-income Ukrainian peasants, mass impoverishment and low standards of living), innovative infrastructure (development of the newest means of communication and large geographical discoveries) that encouraged intercountry resettlement. However, the vector of migratory flows of Ukrainians was rather diverse: Ukrainians under Austro-Hungary (Galicia, Northern Bukovina and Transcarpathian Ukraine) were covered by intercontinental migration (USA, Canada, Brazil and Argentina), while the peasants of the Left Bank and Central Ukraine migrated to the Northern Caucasus and the Far East.

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)0.000
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.228
Teacher spread0.188 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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Same venueÌstorìâ narodnogo gospodarstva ta ekonomìčnoï dumki UkraïniSame topicEconomic Issues in UkraineFrench-language works237,207