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Record W2181689167

Testing for stochastic dominance among additive, multivariate welfare functions with discrete variable

2009· article· en· W2181689167 on OpenAlexfundno aff
Gastón Yalonetzky

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsnot available
FundersBundesministerium für Wirtschaftliche Zusammenarbeit und EntwicklungAustralian Agency for International DevelopmentGeorg-August-Universität GöttingenUniversity of OxfordInternational Development Research CentreEconomic and Social Research CouncilInternational Fine Particle Research InstituteUnited Nations Development ProgrammeRobertson FoundationUNICEF
KeywordsMultivariate statisticsStochastic dominanceEconometricsMathematicsDominance (genetics)Multivariate analysisInstrumental variableVariable (mathematics)StatisticsWelfareEconomicsBiologyMathematical analysis
DOInot available

Abstract

fetched live from OpenAlex

A ‡ourishing literature on robustness in multidimensional welfare and poverty comparisons has aroused the interest on multidimensional stochastic dominance. By generalizing the dominance conditions of Atkinson and Bourguignon (1982)

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)0.041
metaresearch head score (Gemma)0.172
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.172
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.003
Science and technology studies0.0010.004
Scholarly communication0.0030.006
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.034
GPT teacher head0.283
Teacher spread0.249 · 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 designTheoretical or conceptual
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
Published2009
Admission routes1
Has abstractyes

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