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Record W4210284749 · doi:10.1111/imig.12978

Managing the rising tide of Nigerian migrants to the West—A policy vacuum or a structural challenge?

2022· article· en· W4210284749 on OpenAlexaffabout
Philomina Okeke‐Ihejirika, Ike Odimegwu

Bibliographic record

VenueInternational Migration · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDiasporaDestinationsHomelandPoliticsImmigrationPolitical scienceEconomic growthFocus groupPublic policyDevelopment economicsSociologyPolitical economyEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract This analysis explores the growing attraction of migrants to destinations perceived as better pastures as well as the roots and consequences of international migration, especially for irregular migrants. The findings of two focus group discussions with Nigerian scholars, policymakers, service providers, and members of society suggest: (1) public policy on international migration should consider the social, political, and economic challenges that render many Africans desperate to leave the continent regardless of the harsh realities awaiting them along the way or in a new homeland; (2) given the fundamental rights of individuals to migrate, it is crucial that relevant information about the realities of life in Western host societies (especially newer destinations such as Canada) be made available in immigrant‐sending regions, such as Africa; and (3) efforts to engage the new African diaspora should also prioritize their active participation in building equitable societies in their countries of origin.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.007
Scholarly communication0.0110.005
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.333
Teacher spread0.312 · 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 designNot applicable
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

Citations10
Published2022
Admission routes2
Has abstractyes

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