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Record W1590957081 · doi:10.22004/ag.econ.93980

Agricultural Production and Productivity in Canada

2009· article· en· W1590957081 on OpenAlexaboutno aff
Terrence S. Veeman, Richard Gray

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureProductivityLivestockAgricultural productivityAgricultural economicsProduction (economics)EconomicsTotal factor productivityNational economyNatural resource economicsGeographyEconomic growthEconomic systemMacroeconomicsForestry

Abstract

fetched live from OpenAlex

Agriculture in Canada was substantively transformed in the past century.In absolute terms, agricultural production increased considerably.For example, production of wheat, a major Canadian crop, based initially on the improved variety Marquis, trebled from 1908 to 2008.New crops, such as canola-improved varieties of rapeseed-on the Prairies and soybeans in Ontario, are now widely grown.Similarly, the numbers of livestock on farms have greatly increased since World War I, the number of cattle and calves nearly doubling, the number of pigs growing about four-fold, and the number of chickens trebling (Statistics Canada, 2009).In relative terms, however, primary agriculture's share of the Canadian economy has shrunk to account for 1% to 2% of GDP and some 2% of national employment.Such structural change has been common in developed nations.Associated with economy-wide changes in the structure of agriculture, agricultural productivity has increased considerably over time, whether measured in terms of increases in crop yields, livestock gains, or growth in overall-total factor-productivity. An Overview of Canadian AgricultureAgriculture uses only 7% of Canada's land mass and is concentrated in the southern portion of the country, chiefly in the Canadian prairies and the southerly reaches of Ontario and Quebec.The current Canadian farmland area of 67.8 million hectares (mha) has remained relatively constant since World War II, although the area in crops has crept upwards to some 36 mha (Statistics Canada, 2007).In western Canada, since the 1980s, while individual farms have become more specialized, aggregate agriculture has diversified away from cereal and coarse grains, mainly wheat and barley, to higher-valued crops such as oilseeds, chiefly canola, and pulses such as field peas and lentils.In terms of cropped area in Canada, despite having lost ground spring wheat still leads, followed by hay and other fodder crops, with canola now ahead of barley, in third place.

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)0.001
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 score0.245
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.172
Teacher spread0.149 · 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

Citations13
Published2009
Admission routes1
Has abstractyes

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