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Acreage Response to Whole Farm Income Stabilisation Programmes

2012· article· en· W1530312207 on OpenAlex
Samira Bakhshi, Richard Gray

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 · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsSaskatchewan Health
Fundersnot available
KeywordsSubsidyEconomicsPerspective (graphical)Risk aversion (psychology)Production (economics)Public economicsAgricultural economicsExpected utility hypothesisMicroeconomicsFinancial economicsMarket economy

Abstract

fetched live from OpenAlex

Abstract This article investigates whether Canadian whole farm programmes, which fall under the WTO category of Green Box subsidies, are truly production neutral. Theory suggests that with non‐constant risk aversion, risky decisions can be influenced by both the level of expected wealth (i.e. the wealth effect) and the variability of wealth (i.e. the insurance effect). Unlike previous approaches, this article is able to extend a framework developed by Chavas and Holt to formally incorporate the insurance effect into the acreage allocation decisions. By applying the theoretical model to acreage data in the Canadian Prairies, the results reveal that the whole farm income stabilisation programmes had large impacts on acreage choices through wealth and insurance effects. From a WTO perspective, the results underline the inherent difficulty in designing programmes that will reduce the risk faced by farmers without altering behaviour.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.311

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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