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Record W7074245918

FARM LEVEL IMPACT OF ADOPTING MULTIPLE COMPONENT PRICING IN THE APPALACHIAN FMMO AND EVALUATING THE USMCA CANADIAN CREAM TRQ: A GSIM APPROACH

2021· article· en· W7074245918 on OpenAlexaboutno aff

Bibliographic record

VenueUKnowledge (University of Kentucky) · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionHyporeflexiaGestational periodDiafiltrationTSG101Articular cartilage damage
DOInot available

Abstract

fetched live from OpenAlex

This thesis is composed of two essays regarding the dairy industry of North America. The first essay aims to evaluate the adoption of an MCP pricing system in the Appalachian FMMO. Producers in Georgia, Kentucky, Tennessee, and North Carolina have formally voiced concern about adopting MCP due to concerns over reduced milk value. Using cow-level production data from Kentucky, the effect on farm level prices can be estimated. It is determined Jersey cow herd’s milk value under MCP appreciates 9% in Kentucky, while the impact on Holstein herds is dependent on many factors. The second essay evaluates the potential impact of the expanded tariff rate quota for cream in Canada from the implementation of the United States-Mexico-Canada trade agreement. Utilizing a global simulation model for trade using Armington elasticities, the impact of this expanded access can be estimated for both American and Canadian consumers and producers. Canadian imports of American cream are estimated to increase 316% over the first year of the USMCA. This paper includes a review of Canada’s dairy industry and trade relations as relating to the dairy industry.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.971

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.116
GPT teacher head0.242
Teacher spread0.126 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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