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Record W1414231324 · doi:10.1017/cbo9781139942027

Political Identity and Conflict in Central Angola, 1975–2002

2015· book· en· W1414231324 on OpenAlexaboutno aff
Justin Pearce

Bibliographic record

VenueCambridge University Press eBooks · 2015
Typebook
Languageen
FieldSocial Sciences
TopicAfrican studies and sociopolitical issues
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsHegemonyIndependence (probability theory)IdeologyPolitical economyState (computer science)Political scienceIdentity (music)LoyaltyQuarter (Canadian coin)PopulationGender studiesSociologyGeographyLawAesthetics

Abstract

fetched live from OpenAlex

This book examines the internal politics of the war that divided Angola for more than a quarter-century after its independence. It emphasises the Angolan people's relationship to the rival political forces that prevented the development of a united nation, an aspect of the conflict that has received little attention in earlier studies. Drawing upon interviews with farmers, town dwellers, soldiers and politicians in Central Angola, Justin Pearce examines the ideologies about nation and state that elites deployed in pursuit of hegemony and traces how people responded to these attempts at politicisation. The book not only demonstrates the potency of the rival conceptions of state and nation in shaping perceptions of self-interest and determining political loyalty, but also shows the ways in which allegiances could and did change for much of the Angolan population in response to the experience of military force.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.090
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0080.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.289
Teacher spread0.237 · 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

Citations108
Published2015
Admission routes1
Has abstractyes

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