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Record W3186667394

Calculation of the balance of economic benefits and losses from the migration of workers abroad

2019· article· en· W3186667394 on OpenAlexaboutno aff
Sergej Vojtovič, Emília Krajňáková, Magdaléna Tupá

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSocio-economic Development and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceEuropeanisationEuropean unionEconomyEconomicsInternational trade
DOInot available

Abstract

fetched live from OpenAlex

1. Adepoju, A., Van Noorloos, F., Zoomers, A. Europe's Migration Agreements with Migrant-Sending Countries in the Global South: A Critical Review. Journal of International Migration, 2010. (48) 3, p. 42-75. 2. Kazlauskienė, A., Rinkevicius L. The Role of Social Capital in the Highly-Skilled Migration from Lithuania. Engineering Economics, 4, 2006, p. 69-75. 3. Zwysen, W. Different Patterns of Labor Market Integration by Migration Motivation in Europe: The Role of Host Country Human Capital. International Migration Review, 2018, vol. 53, 1: pp. 59-89. 4. Rosenow, K. The Europeanisation of Integration Policies. Journal of International Migration. (47) 1, 2009, p.133-159. 5. Schaeffer, P. Refugees: On the Economics of Political Migration. Journal of International Migration. (48) 1, 2010, p. 1-22. 6. Kordos, M. Role of innovations in the EU industrial policy and competitiveness enhancement. Proceedings of the 2nd international conference on European integration, 2014. Ostrava: VSB, p. 335-342. 7. Daugeliene, R. The position of knowledge workers in knowledge-based economy: migration aspect. European Integration Studies, 1, 2007, p. 103-112. 8. Dagiliene, L., Leitoniene, S., Grencikova, A. Increasing business transparency by corporate social reporting: development and problems in Lithuania. Engineering economics. (25) 1, 2014, p. 54-61. 9. Haviernikova, K., Srovnalikova, P. The immunity of family business in the conditions of economic crisis. Problems of social and economic development of business. Vol. I. Montreal: Breeze,2014, p. 179-183. 10. Carmona, C.; Fluixa, F. M.; Hernaiz-Agreda, N.; Saurin, A. A. N. Educated for migration? Blind spots around labor market conditions, competence building, and international mobility. European Educational Research Journal, 2018, Vol. 17, 6, pp. 809-824. 11. Divinský, B. Labor market – migration nexus in Slovakia: time to act in a comprehensive way. Bratislava: IOM, 2007. 145 s. 12. Statistický Urad SK. VZPS. Avialable at:https://www.google.com/searchq=VZPS%2C+%C5%A0%C3%9A+SR&oq=VZPS%2C+%C5%A0%C3%9A+SR&aqs=chrome..69i57.3417j0j8&sourceid=chrome&ie=UTF-8 [Accessed 2014.12.18]. 13. Spravodajstvo. Available at: http://voyo.markiza.sk/produkt/ spravodajstvo/15473-prezidentske-volby-16-03-2014 [Accessed 2014.03.16]. 14. Vseobecna zdravotna poisťovňa. Available at: http://www.vszp.sk/platitelia/platenie-poistneho/preddavky-poistne/preddavky-poistne-predchadzajuce-obdobia.html [Accessed 2015.06.18]. 15. Slovensko na ceste k rodovej rovnosti.. SU SAV. Available at: http://www.sociologia.sav.sk/cms/uploaded/1147_attach_equal_rovnost_sk.pdf [Accessed 2014.10.27]. 16. Euroekonom. Avialable at: https://www.euroekonom.sk/ekonomika/ekonomika-sr/ 17. Sberbank Slovenska. Available at: http://www.sberbank.sk/servlet/ sberbank?MT=/Apps/Sberbank/WEB/main.nsf/ [Accessed 2015.04.17]. 18. Socialna poisťovňa.. Available at: http://www.socpoist.sk/tabulka-platenia-poistneho-od-1-januara-2013-wta/56200s [Accessed 2015.06.18]. 19. Worldbank. Available at: http://econ.worldbank.org/wbsite/external/extdec/extdecprospects/ [Accessed2015.06.18].

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.013
GPT teacher head0.207
Teacher spread0.195 · 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 designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

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