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Choosing from a Moral Point of View

2001· article· en· W644796199 on OpenAlexaff
Norman Frohlich, oe Oppenheimer

Bibliographic record

VenueJournal of Interdisciplinary Economics · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMoralitySketchEpistemologyRationalitySociologyPoliticsPerspective (graphical)Point (geometry)DemocracyLaw and economicsLawPhilosophyComputer sciencePolitical scienceMathematics

Abstract

fetched live from OpenAlex

The notion of a moral point of view has a distinguished pedigree. But it has been integrated neither into economic modeling nor political philosophy. We make a preliminary attempt to do this. Specifically, we ask: “What is meant, in general, by a moral point of view? What elements are common to all notions of morality?” In asking these questions we do not seek agreement as to the content, and status of morality. Rather, we are interested in squaring the notion of moral points of view with the decision theoretic models at the base of rationality theory. Further, we are concerned to identify those elements which generate the substantive implications of adopting a moral point of view so that one can eventually analyze which aspects of a moral point of view are required by a modem democracy. We sketch a few of the consequences for social decisions if individuals, either unorganized or within a society, chose from such a point of view rather than some other” “How could you possibly have done that?” says Sheila to her friend Betsy, “You really did the wrong thing.” “I don’t really know,” comes the answer. “I guess I just wasn’t thinking about it clearly; I didn’t have the right perspective on it.” Sheila is obviously talking about some bad choice made by Betsy, but it is hard to conclude much more from those few lines. She could be talking about Betsy’s purchase of a hair dryer without some essential feature, or a decision to take Sheila’s car without permission. In either case, it would not be surprising were Sheila to continue advising her friend as follows “You should have considered your decision from a different point of view! Think about …” Economists assume that an individual making a choice has a unique set of values, but recent evidence does not bear this out (Tversky and Kahneman, 1981 & 1986; as well as Shafir and Tversky, 1994; but also see Sen, 1977 and Margolis, 1982 who were early dissenters from the classic economic point of view). Indeed, Betsy’s response indicates that the (offending) choice was made on the basis of a ‘perspective’ or ‘point of view’ which led her to the wrong decision. The implication: a different perspective might have led to the right choice.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.134
GPT teacher head0.409
Teacher spread0.275 · 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 designOther design
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

Citations11
Published2001
Admission routes1
Has abstractyes

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