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Record W3103192925 · doi:10.3982/ecta14953

Cheap Talk With Endogenous Conflict of Interest

2020· article· en· W3103192925 on OpenAlex
Nemanja Antić, Nicola Persico

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

VenueEconometrica · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicGame Theory and Applications
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsCommunication sourceCheap talkMathematical economicsPrincipal (computer security)Competitive equilibriumEconomicsMicroeconomicsSignaling gameSign (mathematics)Information transmissionInverse demand functionSet (abstract data type)Complete informationComputer scienceEconometricsDemand curveMathematicsComputer security

Abstract

fetched live from OpenAlex

In a cheap‐talk setting where the conflict of interest between sender and receiver is determined endogenously by the choice of parameters θ i for each agent i , conditions are provided that determine the sign of each agent's inverse demand for θ without assuming that the most informative equilibrium will necessarily be played in the cheap talk game. For two popular functional forms of payoffs, we derive analytically tractable approximations for agent i 's demand for θ . In an application where the θi 's are purchased on a competitive market, we provide conditions for a competitive equilibrium to feature maximal information transmission. In a principal–agent application where the agent's θ is set by the principal, our results show that information transmission will be partial. We consider extensions where: (1) the θ 's are acquired covertly rather than overtly and (2) the θ 's are traded after the sender has received the information.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.545
GPT teacher head0.371
Teacher spread0.175 · 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