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Record W3018534670 · doi:10.1111/cjag.12244

The COVID‐19 pandemic: Anticipating its effects on Canada's agricultural trade

2020· article· en· W3018534670 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProtectionismAgricultureRecessionEconomicsRevenueAgricultural economicsInternational tradeWorld tradeValue (mathematics)International economicsBusinessGeography

Abstract

fetched live from OpenAlex

Abstract With the deep recession now forecast for the world economy, trade can be expected to fall even more steeply. Agricultural trade will be less significantly affected, being insulated by its relatively low income elasticities of demand. However, a drop in the range of 12%–20% in real trade value should be expected. Canada can be expected to share in this, but, within agricultural exports, cereals will be least affected. This minimal expected impact to cereals stems partly from the risk of wheat export bans by Russia and Kazakhstan, due to increases in wheat prices. Livestock, pulses, and horticulture exporters can be expected to face a larger decline in trade prospects and revenues. An equally large threat, along with falling incomes in our trade partners, is their policy responses, particularly the potential increase in import restrictions. These may take the form of more costly inspections, tightened SPS and food safety regulations, and protectionist measures from competing domestic producers.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.073
GPT teacher head0.206
Teacher spread0.132 · 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