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Pro-poor Economic Development Aid to Haiti: Unintended Effects Arising from the ConflictDevelopment Nexus

2011· article· en· W2025484632 on OpenAlexaff
Yasmine Shamsie

Bibliographic record

VenueJournal of Peacebuilding & Development · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsNexus (standard)Vulnerability (computing)Development economicsEconomic growthPolitical instabilityPovertyUnintended consequencesWork (physics)PoliticsCapital (architecture)Political scienceEconomicsGeography

Abstract

fetched live from OpenAlex

Poverty reduction has been a prominent and critical goal of Haiti's main international donors, yet they have directed little economic aid to rural areas where a large segment of Haiti's poor live and work. Instead, donors have focused on re-establishing a vibrant urban-based manufacturing sector. While sidestepping agriculture is not a new trend, this paper argues that the policy set employed by donors since 2004 – a conflict and development approach that stresses vulnerability to crime and political instability – has served to reinforce the country's historical bias against rural development. While the 2010 earthquake has provided the impetus to decentralise economic activity, it is too soon to know if and how the rural poor will benefit, particularly given continued security-related concerns associated with the capital region.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.049
GPT teacher head0.294
Teacher spread0.245 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2011
Admission routes1
Has abstractyes

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