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Record W1532669686 · doi:10.18174/7207

Learning from Carchi: agricultural modernisation and the production of decline

2009· dissertation· en· W1532669686 on OpenAlexfundno aff
Stephen Sherwood

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
FundersInternational Development Research CentreUnited States Agency for International Development
KeywordsAgricultureModernization theoryGeographyGovernment (linguistics)ProductivityAgricultural productivityPopulationProduction (economics)Agricultural economicsPolitical scienceEconomic growthEconomicsSociologyDemography

Abstract

fetched live from OpenAlex

Provided its natural endowments, generally educated rural population, infrastructure and market access to two countries, the Province of Carchi, located in the northernmost highlands of Ecuador, is potentially one of the most productive agriculture regions in the Andes. In the 1960s development experts and the government targeted the region as a model for agricultural modernisation. Following land reform and rapid organisation around industrial era technologies, potato farming in Carchi boomed during the 1970s, evolving to dominate the landscape and become the major source of livelihoods in the province. By the early 1980s, Carchi came to produce nearly half the national potato harvest on less than a quarter of the country’s area dedicated to the crop. In the early1990s, however, production and productivity began to fall off, leading a growing number of rural families in Carchi to fall into debt and abandon potato farming. The research reported here is the outcome of the author’s ten years of research and development practice in Carchi with the International Potato Center, the FAO’s Global IPM Facility, and World Neighbors. It reflects unfolding experience with different phases of hope, discovery, and ambition. Many aspects of the experience have been published elsewhere (see Appendix A). The resulting dissertation is not a case study in the sense of a case that tests a hypothesis. It is a monograph that attempts to produce a single coherent story over seemingly unrelated events, focusing on a second-generation problem: despite a decade of highly rigorous, scientific research on the pathologies of Carchi and multiple public demonstrations of feasible alternatives, little significant change was achieved.

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)0.000
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 score0.966
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.027
GPT teacher head0.251
Teacher spread0.225 · 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.

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

Citations27
Published2009
Admission routes1
Has abstractyes

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