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Record W2562901458

MIGRATION IMPACT ON ECONOMICAL SITUATION

2016· article· en· W2562901458 on OpenAlexaboutno aff
Virginia Cojocaru, Alexandru Gribincea

Bibliographic record

VenueECONOMY AND SOCIOLOGY: Theoretical and Scientifical Journal · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Socioeconomic and Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)ImmigrationQuarter (Canadian coin)EconomicsShock (circulatory)Labour economicsGeography
DOInot available

Abstract

fetched live from OpenAlex

This paper presents recent trends and flows of labor migration and its impact on economic and social life. Main aim of this research sets up the influence of the migration on the European economics and its competitiveness. Methods of research are: method of comparison, analysis method, method of deduction, method of statistics, modeling method. The economic impact of migration has been intensively studied but is still often driven by ill-informed perceptions, which, in turn, can lead to public antagonism towards migration. These negative views risk jeopardising efforts to adapt migration policies to the new economic and demographic challenges facing many countries. Migration Policy looks at the evidence for how immigrants affect the economy in three main areas: The labour market, public purse and economic growth. In Europe, the scope of labour mobility greatly increased within the EU/EFTA zones following the EU enlargements of 2004, 2007 and 2014-2015. This added to labour markets’ adjustment capacity. Recent estimates suggest that as much as a quarter of the asymmetric labour market shock – that is occurring at different times and with different intensities across countries – may have been absorbed by migration within a year

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.999

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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