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Record W3158303415 · doi:10.1111/cjag.12284

Re‐examining the implications of COVID‐19 on the Canadian dairy and poultry sectors

2021· article· en· W3158303415 on OpenAlexaffvenueabout
Alfons Weersink, Mike von Massow, Brendan McDougall, Nicholas Bannon

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHospitalityBusinessUpstream (networking)Supply chainCoronavirus disease 2019 (COVID-19)Downstream (manufacturing)Agricultural economicsDairy industryPoultry farmingAgribusinessAgricultural scienceMarketingEconomicsTourismFood scienceAgricultureDiseaseGeographyVeterinary medicineEnvironmental scienceEngineeringMedicine

Abstract

fetched live from OpenAlex

Abstract The dairy and poultry sectors responded quickly to the initial adjustments in the quantity and nature of food products forced by the shuttering of the hospitality sector and the subsequent switch to buying food from grocery stores. In addition, these sectors were less affected by the labor availability and health issues from COVID‐19 (coronavirus disease‐2019) that plagued others, such as red meat processors. While the overall impacts were less than most other parts of the agri‐food system, some elements of supply managed products, particularly poultry processors, have experienced a reduction in returns and are still adjusting to the new demand and supply situation. The extent of the impact is correlated with the degree to which the supply chain further upstream was connected to the downstream hospitality sector.

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)0.005
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 score0.070
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.083
GPT teacher head0.210
Teacher spread0.128 · 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

Citations12
Published2021
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomieSame topicCOVID-19 Pandemic ImpactsFrench-language works237,207