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Record W3005131640 · doi:10.1111/cjag.12305

Reforming Canada's dairy supply management scheme and the consequences for international trade

2022· article· en· W3005131640 on OpenAlexaffvenueabout
Brennan A. McLachlan, G. Cornelis van Kooten

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSupply managementBusinessStatus quoHarmProduct (mathematics)International tradeSupply chainBaseline (sea)Dairy industryEconomies of scaleInternational economicsAgricultural economicsEconomicsMarket economyMarketing

Abstract

fetched live from OpenAlex

Abstract Following Carter and Mérel (2016), we explore the export benefits of reforming supply management (SM) in Canada's dairy sector. A trade model with ten regions and five dairy product categories is developed and used to examine the potential benefits of opening international markets to Canadian dairy products. In addition to a baseline, three scenarios are compared—one with SM in place but with Canada able to export freely. Two other scenarios assume SM is eliminated and there is complete free trade, but with high‐ and low‐cost structures. Findings indicate that, in the high‐cost scenario, domestic consumers gain from lower prices as the domestic supply and exports fall compared to the status quo, but producers are less well off. However, under a low domestic cost structure, Canada becomes a major exporter of milk, with both producers and consumers gaining from free trade. This scenario assumes that domestic producers take advantage of economies of scale, enabling them to compete in international markets. Appropriate policies will be required to reform the quota regime, while minimizing the harm done to dairy farmers.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.158
Teacher spread0.143 · 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 designNot applicable
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

Citations2
Published2022
Admission routes3
Has abstractyes

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