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Living in the Move: Impact of Guest Workers on Population Characteristics of the United Arab Emirates (UAE)

2014· article· en· W2758180577 on OpenAlexvenueno aff
Fayez M. Elessawy, Esmat Zaidan

Bibliographic record

VenueArab world geographer · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsCensusWorkforceImmigrationPopulationEconomic growthMigrant workersGeographyDemographic economicsBusinessSocioeconomicsDemographySociologyEconomics

Abstract

fetched live from OpenAlex

This study highlights the effect of immigrant workers on the unprecedented demographic growth in the UAE, which has become one of the highest in the world. The population of the UAE has octupled in 30 years, from 0.5 million in 1975 to 4 million in 2005, leading to a serious demographic imbalance. Using the topical approach, this study investigates the demographic impact of migrant workers on UAE society. The study relies on census data collected between 1970 and 2005 (the most recent census). The study makes recommendations as to how decision makers can tackle the issues resulting from the presence of large numbers of migrant workers. At a time when the number of national university graduates has increased and the range of opportunities to enhance the national workforce has become immense, the essence of these recommendation is to rely less and less on migrant workers and encourage nationals to take on jobs in various areas. Over the next several decades, this will help reduce the presence of foreign mig...

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)0.001
metaresearch head score (Gemma)0.002
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.286
Teacher spread0.271 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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