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Record W2369339626

Reform effects and implications of Canada's agricultural support policy

2014· article· en· W2369339626 on OpenAlexaboutno aff
Zhu Man-d

Bibliographic record

VenueJournal of Hunan Agricultural University(Social Sciences) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureAgricultural policyGovernment (linguistics)BusinessDirect PaymentsAgricultural productivityChinaAdaptabilityEconomic policyInstitutionEconomic growthEconomicsAgricultural economicsPaymentFinancePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Canada government constructs the package of agricultural policies through continually policy reform from the 1930 s, which current takes Growing Forward 2 Policy Framework as the core of agriculture. Using producer support estimates(PSE) method to assessment Canada's agricultural support policy reform, the result shows Canada's agriculture sector is full of innovation, dynamic, competitiveness and adaptability due to supporting by business risk management(that is BMR) and Non-BMR programme for agriculture. There are important implications for China's agricultural support policies reform in transition period, such as: form the integration agricultural support policy which joint the central government, provincial government and county government through agricultural management institution reform, construct business risk management for agricultural and take advantage of market price support measures and direct payments linked agricultural production through the polices optimization, protect the sensitive products and support to improve agricultural competitiveness, adaptability and sustainable development programme.

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)0.003
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.983

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0060.003
Scholarly communication0.0050.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.003
GPT teacher head0.174
Teacher spread0.171 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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