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W<scp>hole</scp> F<scp>arm</scp> I<scp>ncome</scp> I<scp>nsurance</scp>

2011· article· en· W2005224995 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Risk & Insurance · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
Fundersnot available
KeywordsIndemnityCrop insuranceSubsidyRevenueAgricultural scienceBusinessActuarial scienceEconomicsAgricultureAgricultural economicsFinanceEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

Abstract This article employs a mathematical programming model to investigate farmers’ optimal crop choices under gross revenue insurance, whole farm income insurance (WFI), the Canadian Agricultural Income Stabilization (CAIS) program, and its modified 2008 program AgrInvest. WFI poses a particularly interesting problem since the indemnity/premium structure is dependent upon the choice of crops, whereas the choice of crops is simultaneously influenced by the presence of the whole farm insurance program. Results indicate that farmers will alter farm plans significantly in response to the type of insurance offered and the level of subsidy.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.003
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0030.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.018
GPT teacher head0.214
Teacher spread0.197 · 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