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Record W2898331662 · doi:10.3982/te2547

Strategy-proof tie-breaking in matching with priorities

2018· article· en· W2898331662 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTheoretical Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGame Theory and Voting Systems
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMatching (statistics)Computer scienceMathematical economicsEconomicsMathematics

Abstract

fetched live from OpenAlex

A set of indivisible objects is allocated among agents with strict preferences. Each object has a weak priority ranking of the agents. A collection of priority rankings, a priority structure, is solvable if there is a strategy-proof mechanism that is constrained efficient, i.e., that always produces a stable matching that is not Pareto-dominated by another stable matching. We characterize all solvable priority structures satisfying the following two restrictions: Either there are no ties or there is at least one four-way tie.For any two agents i and j, if there is an object that assigns higher priority to i than to j, there is also an object that assigns higher priority to j than to i.(A)(B) We show that there are at most three types of solvable priority structures: The strict type, the house allocation with existing tenants (HET) type, where, for each object, there is at most one agent who has strictly higher priority than another agent, and the task allocation with unqualified agents (TAU) type, where, for each object, there is at most one agent who has strictly lower priority than another agent. Out of these three, only HET priority structures are shown to admit a strongly group-strategy-proof and constrained efficient mechanism.

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.

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)0.001
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 score0.176
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.217
Teacher spread0.196 · 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