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Record W2006608067 · doi:10.5539/jas.v5n3p45

Technical Efficiency of Dairy Farms: A Stochastic Frontier Application on Dairy Farms in Jordan

2013· article· en· W2006608067 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsnot available
Fundersnot available
KeywordsInefficiencyProduction (economics)FrontierAgricultural scienceProduction–possibility frontierMilk productionAgricultural economicsStochastic frontier analysisBusinessSample (material)Dairy farmingEconomicsEnvironmental scienceGeographyAnimal scienceMicroeconomics

Abstract

fetched live from OpenAlex

The present study was conducted to determine the level of technical efficiency of dairy producing farms in Jordan by applying the stochastic production frontier (SPF) methodology. Technical efficiency estimates were generated for 100 dairy farms in Jordan. The results of the study indicated that technical efficiency of milk production by most of dairy farms in Jordan is low. The mean technical efficiency was estimated to be only 39.5% for the sampled dairy farms. This means that an average farm in the sample could in principle increase its level of milk production by 60.5% using the current input quantities. The results also implies that the dairy farms in Jordan are producing milk to only about 40% of the potential frontier production levels of this industry, implying that the production is about 60% below the frontier due to technical inefficiency. To enhance farm efficiency there is a need to improve farmers’ access to extension services. The need to involve farmers more in the extension process itself should be encouraged.

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)0.006
metaresearch head score (Gemma)0.004
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 score0.957
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.007
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.024
GPT teacher head0.317
Teacher spread0.293 · 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