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Record W803144238 · doi:10.1111/1756-2171.12326

Contracting with private rewards

2020· article· en· W803144238 on OpenAlexafffund
René Kirkegaard

Bibliographic record

VenueThe RAND Journal of Economics · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsMoral hazardIncentiveMicroeconomicsReservationPrincipal (computer security)Private information retrievalBalance (ability)Benchmark (surveying)Work (physics)EconomicsConstraint (computer-aided design)Function (biology)Principal–agent problemParticipation constraintBusinessComputer scienceMathematicsFinanceComputer securityEngineering

Abstract

fetched live from OpenAlex

Abstract The canonical moral hazard model is extended to allow the agent to face endogenous and noncontractible uncertainty. The agent works for the principal and simultaneously pursues outside rewards. The contract offered by the principal thus manipulates the agent's work–life balance. The participation constraint is slack whenever it is optimal to distort the agent's work–life balance away from life compared to a symmetric‐information benchmark. Then, the agent's expected utility is high and he faces flatter incentives. Such contracts may be optimal when the two activities are strong substitutes in the agent's cost function or when reservation utility is low.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.937
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.188
GPT teacher head0.356
Teacher spread0.168 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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