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Record W2149160094 · doi:10.4038/sjae.v9i0.1830

General Equilibrium Impacts of Technological Change under Different Market Structures: A Comparison of Supply Managed and Other Primary Agricultural Markets in Canada

2010· article· en· W2149160094 on OpenAlexaboutno aff
Pahan Prasada

Bibliographic record

VenueSri Lankan Journal of Agricultural Economics · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsComputable general equilibriumEconomicsEconomic rentAgricultureConsumption (sociology)Technological changeAgricultural economicsRelative priceProductivityGeneral equilibrium theoryPartial equilibriumMacroeconomicsMarket economy

Abstract

fetched live from OpenAlex

Market impacts of technological change in Canadian agriculture are measured within a CGE framework using 2001 input-output data with agriculture disaggregated to six sectors and thirteen commodities. Technological change is modelled as productivity rises in the use of intermediate inputs and of primary factors. Impacts on output, intermediate use of output, foreign trade, final consumption, returns to primary factors and relative price are calculated for primary and processed food products. Impacts of technological change can be summarised into two general outcomes. First, supply managed sectors respond to technological change differently than other agricultural sectors. In the former, economic rents generated from quotas increase while in the latter, outputs, exports, and final consumption increase along with declines of relative supply prices. Second, large relative price declines for other commodities lead to consumer gains. DOI: 10.4038/sjae.v9i0.1830 Sri Lankan Journal of Agricultural Economics, Vol. 9, 2007 pp.1-21

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.207
Teacher spread0.192 · 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 designSimulation or modeling
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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSri Lankan Journal of Agricultural EconomicsSame topicAgricultural Economics and PolicyFrench-language works237,207