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Record W2092434755 · doi:10.1002/jid.1611

Liberalisation and poverty in Africa since 1990–Why is the operation of the ‘invisible hand’ uneven?

2009· article· en· W2092434755 on OpenAlex

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

VenueJournal of International Development · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsDynamic Systems Analysis (Canada)
FundersInternational Fund for Agricultural Development
KeywordsPeasantLiberalizationPovertyEconomicsPoverty reductionFrontierStructural adjustmentDevelopment economicsCorporate governancePoliticsInternational economicsMarket economyEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Abstract The dramatic reduction in poverty in Uganda and Ghana in the 1990s was derived largely from the liberalisation of the export price received by a labour‐intensive peasant export sector. Other African economies ought to be able to derive inspiration from this manifestation of the invisible hand, but can they? Several other African peasant export economies experienced price liberalisation during the structural adjustment period, but without experiencing anything like the same positive poverty reduction dynamic. Two reasons are fairly clear—liberalising countries varied in the extent to which they passed on higher export prices, and they also varied in the extent to which they impacted on dimensions of governance, especially the politics of market access, in the rest of the economy. The latter continues to be an important research frontier for future investigators. Copyright © 2009 John Wiley & Sons, Ltd.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.021
GPT teacher head0.273
Teacher spread0.252 · 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