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Record W2913282340 · doi:10.1093/aepp/ppy038

Reforming Canada's Dairy Sector: USMCA and the Issue of Compensation

2018· article· en· W2913282340 on OpenAlexfundaboutno aff
G. Cornelis van Kooten

Bibliographic record

VenueApplied Economic Perspectives and Policy · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsnot available
FundersCanada Research ChairsCanadian Dairy Commission
KeywordsSupply managementObstacleBusinessAgricultural economicsDairy industryCompensation (psychology)AgricultureEconomicsInternational tradeAgricultural scienceNatural resource economicsGeographyEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Supply management (SM) in Canada's dairy sector was an obstacle to the successful renegotiation of the North American Free Trade Agreement. Reform of agricultural SM regimes in sugar, peanuts, tobacco, and dairy in various jurisdictions are reviewed, and an analytic framework is developed to investigate how Canada might eliminate its dairy quota regime while not overcompensating producers. Compensation based on quota values amount to $5.9 billion if untargeted, but only $2.9 billion if targeted; in contrast, theoretically correct estimates of the loss that dairy producers would face range from $0.2 to $1.9 billion. Such costs are low enough not to impede the elimination of supply management.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.124
Threshold uncertainty score0.901

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0060.004
Scholarly communication0.0080.002
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2018
Admission routes2
Has abstractyes

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