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Record W2240935558

Persons and Their Well-Being: A Critical Discussion of Kaplow and Shavell's Fairness Versus Welfare

2004· article· en· W2240935558 on OpenAlexaff
Hamish Stewart

Bibliographic record

VenueSSRN Electronic Journal · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWelfareNormativeEconomicsPremiseEconomic JusticeSocial WelfareValue (mathematics)Public economicsLaw and economicsMicroeconomicsPolitical scienceLawMarket economy
DOInot available

Abstract

fetched live from OpenAlex

At the heart of any legal policy decision is a set of value judgments about the state of the world we live in. Justice, fairness and social welfare are concepts that play varying roles in these decisions. Welfare economics, a subset of economic theory, imparts a normative framework to the decisions, by examining economic activities at an individual level, in an attempt to maximize aggregate social welfare.As distinguished researchers in the field of economic analysis, Louis Kaplow and Steven Shavell have generated a plethora of debates with the release of Fairness versus Welfare. Their central claim is the proposition that the sole decision-making criterion for creating legal policy must be aggregate well-being; other factors, such as fairness or justice, will bring an undesirable result. Accordingly, individuals are not seen as holders of rights, but as depositories of well-being.The author challenges the validity of Kaplow and Shavell's thesis on a number of grounds. First, their claim requires a clear conception of individual well-being. But in his view it does not; accordingly, their central premise is undermined. Second, he argues that the authors define fairness in a circular way that supports their thesis; that is, they define it as anything that does not increase aggregate welfare. Finally, the author notes that Kaplow and Shavell purport to care about individual well-being but are willing to sacrifice any individual in order to achieve a higher aggregate amount of well-being--in effect, treating individuals as things, or means to an end, rather than as the beneficiaries of the exercise.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.719

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.297
Teacher spread0.282 · 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 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

Citations1
Published2004
Admission routes1
Has abstractyes

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