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Record W2261668184 · doi:10.1080/08263663.2015.1130293

Peasant balances, neoliberalism, and the stunted growth of non- traditional agro-exports in Haiti

2016· article· fr· W2261668184 on OpenAlexaff
Marylynn Steckley, Tony Weis

Bibliographic record

VenueCanadian Journal of Latin American and Caribbean Studies / Revue canadienne des études latino-américaines et caraïbes · 2016
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsWestern University
Fundersnot available
KeywordsPeasantLivelihoodAutonomyCapital (architecture)Government (linguistics)PoliticsNeoliberalism (international relations)Agrarian societyParticipant observationSociologySymbolic powerEconomic growthPolitical economyPolitical scienceDevelopment economicsEconomicsAgricultureSocial scienceGeographyLaw

Abstract

fetched live from OpenAlex

This paper examines divergent peasant responses to models of export-oriented mango production that have been promoted in post-earthquake Haiti. While critical agrarian studies tends to focus more on the ways that capital shapes conditions facing peasant producers, there has been much less attention to the ways that peasant decision-making can restrict how capital operates. This paper argues that Haitian peasants strive to pursue their livelihoods in ways that are at odds with the ambitions of the country’s political and economic elites, and highlights some of the ways that peasants are pushing back against exploitative arrangements to maintain a degree of autonomy over their cropping systems. The field research that forms the empirical basis of this paper was conducted between November 2010 and July 2013 and included: qualitative interviews with leaders of peasant and other rural community organizations, Haitian government officials, and representatives of multilateral institutions; focus groups with peasant farmers; and participant observation.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
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 head0.035
GPT teacher head0.224
Teacher spread0.189 · 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 teacher head, not a consensus.

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

Citations10
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Latin American and Caribbean Studies / Revue canadienne des études latino-américaines et caraïbesSame topicAgriculture, Land Use, Rural DevelopmentFrench-language works237,207