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Record W2468669120 · doi:10.1111/1477-9552.12309

The Local Impacts of Agricultural Subsidies: Evidence from the Canadian Prairies

2018· article· en· W2468669120 on OpenAlex
Ray D. Bollman, Shon Ferguson

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Agricultural Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsBrandon UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsSubsidySpillover effectAgricultureRevenueAgricultural economicsAsset (computer security)EconomicsBusinessNatural resource economicsGeographyFinanceMarket economyMacroeconomics

Abstract

fetched live from OpenAlex

Abstract We estimate the impact of removing an export subsidy on the local economies of Alberta, Saskatchewan and Manitoba, exploiting the large regional variation of a 1995 reform. We find that the loss of the subsidy resulted in significantly lower farm value‐added, farm asset values and local non‐farm employment. The results suggest that the subsidy removal had detrimental spillover effects on the local non‐agricultural economy that varied spatially across the Prairies. The point estimates suggest that the marginal effect of the subsidy loss on non‐agricultural employment was five times as large as those obtained from traditional estimates of the multiplier effect.

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)0.000
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 score0.391
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.045
GPT teacher head0.206
Teacher spread0.161 · 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