MétaCan
Menu
Back to cohort
Record W2221667569 · doi:10.22004/ag.econ.157407

Cost Structure of the Ontario Dairy Industry Revisited: Distributional Aspects

2013· preprint· en· W2221667569 on OpenAlexaboutno aff
Predrag Rajsic

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2013
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsProfit (economics)RevenueSustainabilityAgricultural scienceDairy industryCost structureBusinessAgricultural economicsEconomicsMicroeconomicsFinanceEnvironmental science

Abstract

fetched live from OpenAlex

The initially stated objective of the Canadian dairy supply management–farm revenue risk reduction–has been met well by the program. However, it is less clear whether the program has served all farms equally well. Namely, it is not known how successful the program was in enhancing the cost-effectiveness of smaller farms. This paper uses the 2006 Ontario dairy farm-level accounting data to compare the estimated cost structure with that identified by Moschini (1988). Next, farm size and profit distribution changes are assessed. Finally, the paper provides a simple framework for examining the relationship between current farm size and quota purchases by individual farms. The results suggest that the general cost pattern identified in the early 1980s has been retained. Average cost declines as output increases at lower output levels. However, the minimum-cost farm size has increased about threefold. Additionally, both output and profit distributions have become more skewed, with a lesser contribution by smaller farms. There is evidence that the possibility of quota exchange facilitated the greater expansion of larger farms and that the process of divergence in size and profit between small and large farms is continuing. These results have bearing on the sustainability of smaller farms.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.992

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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.041
GPT teacher head0.222
Teacher spread0.181 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAgEcon Search (University of Minnesota, USA)Same topicAgricultural Economics and PolicyFrench-language works237,207