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Refugees in Violent Decolonizations

2023· book-chapter· en· W4388826621 on OpenAlexaff
Phi-Vân Nguyễn

Bibliographic record

VenueOxford University Press eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsUniversité de Saint-Boniface
Fundersnot available
KeywordsLegitimacyRefugeeAdversaryPopulationPoliticsPolitical scienceCollateral damagePolitical economyPower (physics)State (computer science)Development economicsSociologyCriminologyComputer securityLawEconomics

Abstract

fetched live from OpenAlex

Abstract Refugee flows are not only an important consequence of violent decolonizations. Population movements also affect belligerents’ access to human resources, food, or information. In the case of competing groups vying for power, the arrival or departure of the population may also reinforce or diminish their political legitimacy. In the case of the Vietnam wars, competing factions engineered population movements and instrumentalized their representations to undermine their opponent. Contrary to the idea that population movements are collateral damage, the politics of refugee protection in violent decolonization underscore their importance in sustaining an armed effort and backing the legitimacy of a nascent and oft-contested nation-state.

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: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.027

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 studies0.0040.009
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.031
GPT teacher head0.265
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 designQualitative
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
Published2023
Admission routes1
Has abstractyes

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