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Record W4212951347 · doi:10.18356/fe892629-en

Migration trends in Sub-Saharan Africa (SSA)

2005· book-chapter· en· W4212951347 on OpenAlexaboutno aff

Bibliographic record

VenueWorld Migration Report · 2005
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeGeographyQuarter (Canadian coin)PopulationSocioeconomicsDemographyEconomicsSociologyArchaeology

Abstract

fetched live from OpenAlex

Africa accounts for one-quarter of the world’s land mass and one-tenth of its population, and is the continent with the most mobile populations in the world (Curtin, 1997). In 2000, there were 16.3 million international migrants in Africa, accounting for some 9 per cent of global migrant stocks. Refugees have always been an important factor, but by 2000 both the numbers and the global share of refugees had declined from, respectively, 5.4 million or 33 per cent in 1990, to 3.6 million or 22 per cent. During that same period, the number of non-refugee migrants rose by nearly 2 million to reach 12.7 million in 2000 (UN, 2003). The proportion of females among the 16.3 million international migrants rose from 42 per cent in the 1970s to 46 per cent in the 1990s, and to 46.7 per cent in 2000 (Zlotnik, 2004).

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.042
GPT teacher head0.248
Teacher spread0.207 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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