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Record W3085833883

THE POSSIBLE AND NEGATIVE EFFECTS OF THE POPULATION’S MIGRATION PROCESS IN MACEDONIA AND THEIR REFLECTIONS IN THE BUDGET OF THE COUNTRY

2018· article· en· W3085833883 on OpenAlexaboutno aff
Fauzi Skenderi, Resul Hamiti

Bibliographic record

VenueKnowledge International Journal · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Socioeconomic and Political Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationPoliticsState (computer science)PhenomenonDevelopment economicsPolitical scienceHuman migrationInternal migrationGeographyEconomyEconomicsSociologyLaw
DOInot available

Abstract

fetched live from OpenAlex

This article focuses on the very current social phenomenon of the territories where we live today, called the migration of the population. The migration processes of the population in Macedonia and their reflection on the country's budget, the country's economic situation, the economic situation, the causes of migration, the economic consequences of the state, state benefits, internal migration and dealing with migration as an unstoppable process are the points discussed and developed in the paper.Migrations exist from the very early existence of the human race, as throughout history, man has migrated uninterruptedly, even over long periods of time, only to provide better living conditions. Even though many things have changed from thousands of years ago, there are still many reasons why people choose to migrate to other countries. They could be economical, political, or geographical reasons.Nevertheless, migrations in today's Macedonia have a long history, damaged by various occupiers such as the Roman, Byzantine, Ottoman, Yugoslav, etc.Because of the unpredictable economic and security situation, as in the past, as well today, migrations have not stopped, continue to happen today, right across the European Union and the countries of the Atlantic, such as Canada, the US and Australia, where there are better conditions for life.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.273
Teacher spread0.263 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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