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Record W4253878125 · doi:10.1057/9780230246799_7

Guinea

2009· book-chapter· en· W4253878125 on OpenAlexaff
James Milner

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2009
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAfrican history and culture analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsSierra leoneRefugeeNew guineaSpanish Civil WarHuman settlementGeographyEthnologyPolitical scienceHistoryArchaeology

Abstract

fetched live from OpenAlex

For most of the 1990s, Guinea was an island of relative stability, as conflict and warlordism engulfed its southern neighbours, Liberia and Sierra Leone. From the first arrival of refugees from the Liberian civil war in January 1990, through the outbreak of the Sierra Leonean conflict in 1991, the 1997 coup d’état in Freetown and the resumption of the Liberian war in 1999, Guinea provided refuge for well over 500,000 refugees. Many of these refugees lived in a patchwork of settlements in Southern Guinea, and most became self-sufficient. The refugee programme in Guékédou, Southern Guinea, was UNHCR’s largest refugee programme in Africa in 1999. For many, it was also the most successful. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.156
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1560.031

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 head0.022
GPT teacher head0.256
Teacher spread0.234 · 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
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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