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Record W2402518329 · doi:10.1142/s0217590816400142

REFERENCE DEPENDENCE AND OTHER BEHAVIORAL FINDINGS: THE LIKELIHOOD OF SERIOUS EVALUATION AND POLICY BIASES

2016· article· en· W2402518329 on OpenAlexaff
Jack L. Knetsch

Bibliographic record

VenueThe Singapore Economic Review · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPresumptionEconomicsEquivalence (formal languages)Public economicsWelfareEconometricsActuarial sciencePolitical science

Abstract

fetched live from OpenAlex

Standard economic theory correctly prescribes willingnes-to-pay (WTP) to most accurately assess the welfare change of gains and WTA to measure the welfare change of losses, and, in recognition of reference dependence, reductions of losses. However, its additional assumption of near equivalence between the measures, used to justify the current practice of using WTP for essentially all analyses, has been contradicted by numerous empirical tests. For many areas, and especially environmental quality and health and safety, this institutionally encouraged continuing reliance on presumption over evidence likely leads to serious bias in benefit-cost and related analyses and distortions in policy guidance.

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)0.002
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 score0.518
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.192
GPT teacher head0.319
Teacher spread0.127 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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