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Record W7019215383

Extraregional Migration In The Americas: Profiles , Experiences, and Needs

2020· article· en· W7019215383 on OpenAlexaboutno aff

Bibliographic record

VenueFlorida International University Digital Commons (Florida International University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsMesoamericaWestern hemisphereHuman migrationDocumentationPopulationInternal migrationLatin Americans
DOInot available

Abstract

fetched live from OpenAlex

The International Organization for Migration (IOM), through the Western Hemisphere Regional Migration Capacity-Building Program covering Mesoamerica and the Caribbean, has developed the present study in order to provide an updated description of extraregional migration across the Americas. BACKGROUND • The number of extraregional migrants from Africa, Asia and the Caribbean in Mesoamerica – Central America and Mexico – has increased in recent years. These migrants tend to use both regular means of entry as well as routes associated with smuggling of migrants and irregular border crossing points. • Information on extraregional migrants is scarce, as it is difficult to gain access to this population. Available documentation focuses on two aspects: describing extraregional migrant groups and mapping their main travel routes to the United States and Canada. • The purpose of this report is to describe the main experiences and needs of a group of over 350 extraregional migrants across three sections of their migration route: South America, Central America and Mexico.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.242
Teacher spread0.212 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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