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Record W4414265797 · doi:10.11647/obp.0490.01

1. Collective choice with known preferences

2025· book-chapter· en· W4414265797 on OpenAlexaff
Martin J. Osborne

Bibliographic record

VenueOpen Book Publishers · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCondorcet methodPreferencePreference relationSocial choice theoryProperty (philosophy)VotingTransitive relationApproval votingRelation (database)

Abstract

fetched live from OpenAlex

A group of individuals has to choose an alternative. The individuals disagree about the desirability of the options; their preferences are known. Does a mechanism exist to select an alternative that depends on the individuals' preferences in a reasonable fashion? If only the individuals' ordinal preferences are known, then when the number of alternatives is two, majority voting is the only mechanism that satisfies a short list of appealing properties. When there are three or more alternatives, the existence of an alternative that beats head-to-head every other alternative, known as a Condorcet winner, is significant. If every collective choice problem that the individuals may face has a Condorcet winner, then the mechanism that selects that alternative is the only one that satisfies a short list of attractive properties. Otherwise, no such mechanism generally exists. A related question is whether a mapping exists from profiles of the individuals' preference relations to a preference relation for the group that satisfies some reasonable properties. If for every profile of preference relations that is possible for the group a Condorcet winner exists, then such a mapping associates with each profile of preference relations the preference relation in which one alternative is preferred to another if and only if it is preferred by a majority of individuals. If all profiles of logically possible preference relations are possible, no such mapping exists. If the individuals' preference intensities are known and can be compared then the only ordering of welfare profiles that satisfies a specific equity property ranks these profiles according to the welfare of the worst-off individual. If welfare differences, but not levels, can be compared across individuals, then the utilitarian ordering results.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.279
Teacher spread0.228 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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