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Record W2067213468 · doi:10.1080/03056240500121032

Sierra Leone: Urban-elite bias, atrocity & debt

2005· article· en· W2067213468 on OpenAlex
Barry Riddell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReview of African Political Economy · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsQueen's University
Fundersnot available
KeywordsSierra leoneElitePeasantDebtPolitical scienceDevelopment economicsColonialismGovernment (linguistics)State (computer science)Economic growthEconomicsLawFinancePolitics

Abstract

fetched live from OpenAlex

Sierra Leone experienced the violent results of an undeclared civil war which lasted over a decade. The state had lost control of the country's hinterland! Maiming, killing, and destruction dominated this part of West Africa, and the violence largely resulted from a set of programmes and policies of the country's post-colonial government which produced pronounced and obscene elite-peasant disparities. With the termination of hostilities, the IMF and the World Bank have financially assisted the country's recovery and rehabilitation through a set of programmes. These were dominated by the IMF's Post-Conflict scheme and the jointly-administered (IMF/WB) Heavily Indebted Poor Countries (HIPC) initiative. This paper interrogates the documents of these International Financial Institutions (IFIs) and queries such data in two senses: a) has the nation's development agenda been able to recover from the debt overhang, and b) are the fundamental causes of the country's violent past addressed? The experience of Sierra Leone provides a window into the operations of the IFIs as they impose neoliberal globalisation in the third world.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.322
Teacher spread0.285 · 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