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Record W3141165076

Rural Organizations, Agricultural Technologies and Production Efficiency of Teff in Ethiopia

2015· article· en· W3141165076 on OpenAlexaff
Getu Hailu, Alfons Weersink, Bart Minten

Bibliographic record

Venue2015 Conference, August 9-14, 2015, Milan, Italy · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsInefficiencyProduction (economics)AgricultureAgricultural economicsService (business)Variable (mathematics)EconomicsProduction efficiencyBusinessAgricultural engineeringMathematicsGeographyEconomyMicroeconomicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

We study the production efficiency of teff in Ethiopia. Using a large cross-section of teff plots, we find that teff output could be increased by approximately 25 percent with the available inputs and technology through investments directed to improved gender-sensitive extension service and infrastructure development. The magnitude of technical inefficiency is robust to alternative functional form and various variable specifications. Community discussion groups and distance to the nearest agricultural co-operative are further shown to have a significant effect on technical efficiency. We conclude the paper by discussing the potential policy implications of our findings.

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)0.001
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 score0.742
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.245
Teacher spread0.226 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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