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Record W7117118692 · doi:10.1080/15378020.2025.2606674

The role of policy in enhancing beef production and marketing in Maritime Canada

2025· article· en· W7117118692 on OpenAlexaffabout
Chanuka Swarnathilake, Leo-Paul Dana, Gumataw Kifle Abebe

Bibliographic record

VenueJournal of Foodservice Business Research · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsDalhousie University
Fundersnot available
KeywordsProduction (economics)Public policySustainabilityAgribusinessProduction manager

Abstract

fetched live from OpenAlex

This study evaluates the effectiveness of policy frameworks that support Maritime Canada’s beef sector, and the regional food service industry by adopting the New Institutional Economics (NIE) theory A thematic content analysis was conducted using 31 policy documents in MAXQDA. It was found that current policies support sustainable beef production and marketing and, indirectly, impact the food service sector. Opportunities exist to enhance local meat sourcing and supply chain stability for restaurants and institutional buyers. The policy instruments influence sourcing costs and supply chain resilience in the foodservice sector by improving production efficiency and fostering local market integration.

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)0.005
metaresearch head score (Gemma)0.002
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 score0.498
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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
Published2025
Admission routes2
Has abstractyes

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