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Technical Efficiency, Technological Change and Output Growth of Wheat Farms in Saskatchewan

2001· article· en· W2116391861 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsProductivityAgricultural scienceWelfare economicsProduction (economics)Technical progressTechnical changeAgricultural economicsForestryEconomicsMathematicsGeographyEnvironmental scienceEconomic growth

Abstract

fetched live from OpenAlex

This paper utilizes recent advances in stochastic decomposition methodology to examine the level and the driving forces of technical efficiency for an unbalanced panel data set of 100 wheat farms in Saskatchewan during the period 1987–95. The contributions of resource use and total factor productivity to the output growth of these farms are also investigated. The analysis indicates moderate levels of technical efficiency and a considerable variation of efficiency ratings among Saskatchewan farms. The ownership status, composition of labor employed, participation in crop insurance and government income transfer programs, participation in Top Management Workshops, degree of specialization, level of intensification and mechanization of production, type of land used, and the farm debts account for differences in efficiency across wheat farms. Even though the productive efficiency of the farms has been increasing over time, the results show that technological progress was the main source of productivity and output growth during the study period. L'analyse que voici fait appel aux plus récentes améliorations apportées à la méthode de décomposition stochastique pour déterminer le degré d'efficacité technique et les motivations d'ungroupe non pondéré de 100 producteurs de blé de la Saskatchewan entre 1987 et 1995. Les auteurs ont aussi déterminé dans quelle mesure l'exploitation des ressources et la productivité totale des facteurs affectent la croissance de la production dans les exploitations concernées. L'analyse révéle un degré moyen d'efficacité technique et une variation considérable du rendement chez les agriculteurs de la Saskatchewan. La variation du rendement s'explique par divers facteurs comme le type de propriété, la composition de la main‐d'œuvre, l'inscription aux programmes gouvernementaux d'assurance récolte et de transfert du revenu, la participation à des ateliers de gestion, le degré de spécialisation, le niveau d'industrialisation et de mécanisation de la production, le genre de terres cultivées et la dette de l'exploitant. Même si la productivité des fermes a augmenté au fil des ans, les résultats indiquent que le progrés de la technologie demeure la principale source d'une croissance du rendement et de la production durant la période à l'étude.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.071
GPT teacher head0.236
Teacher spread0.165 · 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