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THE IMPACT OF WAR-INDUCED FORCED MIGRATION ABROAD ON THE STATE OF UKRAINE'S LABOR POTENTIAL IN THE CONTEXT OF SOCIAL SUSTAINABILITY

2023· article· en· W4387270923 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

VenuePROBLEMS AND PROSPECTS OF ECONOMIC AND MANAGEMENT · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor Market and Education
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianEmigrationRefugeeContext (archaeology)OperationalizationImmigrationQualitative propertySustainabilityWorld War IIState (computer science)Demographic economicsPolitical scienceDevelopment economicsEconomySociologyGeographyEconomicsLaw

Abstract

fetched live from OpenAlex

The labor potential is an important component of the country's economic potential, and its quan-titative and qualitative characteristics significantly affect the rate of economic growth and social sus-tainability. The article presents the general theoretical foundations of the concept of social sustainabil-ity, the main milestones of its formation, key principles and concepts. The information base for the study of migration flows and their expected impact on the qualitative and quantitative characteristics of the labor potential was based on statistical data from Ukraine and countries that have provided asylum to forced migrants. The results of sociological surveys were also used, dozens of which were conducted by international organizations, foreign and Ukrainian think tanks during the war year. An analysis of the available estimates and reservations to them allowed us to formulate the author's assumption about the real number of refugees from Ukraine who have taken refuge in Europe, the United States, and Canada, as well as voluntarily or forcibly ended up in the Russian Federation. The socio-demographic charac-teristics of those who left indicate a significant outflow of working-age people, including a large number of highly skilled workers. A serious risk is posed by the emigration of children and young people, and their failure to return threatens the Ukrainian economy not only with a reduction in labor supply in the near future, but also with a deterioration in its quality characteristics and a loss of Ukraine's demo-graphic potential in the medium and long term. The massive out-migration of the population had a negative impact on effective demand, which is an important driver of the economy.The author proves the expediency of formulating and implementing the state policy of Ukraine aimed at counteracting these negative challenges, which is a prerequisite for ensuring social sustaina-bility. During the period of military operations and post-war recovery, state policy measures in the area of preserving and utilizing labor potential should be as effective as possible and aimed at creating a favorable environment for the return of war refugees to Ukraine and their reintegration into Ukrainian society.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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