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Record W2767772406

The Farm Level Economic Impacts for Western Canadian Cow-Calf Producers Accessing the EU Market

2017· dissertation· en· W2767772406 on OpenAlexaboutno aff
Amanda Lee Gabruch

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2017
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCow-calfAgricultural economicsBusinessAgricultural scienceNatural resource economicsEconomicsEnvironmental scienceAnimal scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

The Canadian beef industry applauded the recent signing of the Comprehensive Economic and Trade Agreement, which will enable greater to access the valuable EU beef market. Despite the enthusiasm surrounding this trade opportunity, the commercial viability of producing for the EU market is still unknown for the cow-calf sector. Thus, the objective of this research is to estimate the premium required by cow-calf producers so that the benefit of enrolling in the EU program for certifying growth enhancing product free beef would outweigh the additional production costs. To address this objective, a break-even (BE) price is simulated under various production scenarios before and after the necessary adjustments are made to become EU compliant. The difference between these simulated break even prices represents an estimate of the required premium. Producers must be offered at least this premium to overcome the additional production costs imposed for compliance. The resulting estimates suggest that the BE difference ranges from $2.13 to $34.78 per calf, depending on the practices already in place prior to enrolling. Given the market conditions over the past decade, premiums as high as $60.12 per head would be required for some producers to maintain their profitability. Besides quantifying costs for EU certification, this research speaks to a greater narrative on the economic considerations of accessing new markets that require certain production attributes. Although these markets may offer higher values, it is important to balance potentially larger revenues with additional costs. Thus, this research offers a framework by which the impact of changing production regimes on profit may be simulated.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.029
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.001
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 head0.017
GPT teacher head0.189
Teacher spread0.172 · 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 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
Published2017
Admission routes1
Has abstractyes

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