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Record W2188657252 · doi:10.1287/mnsc.2015.2349

Intertemporal Uncertainty Avoidance: When the Future Is Uncertain, People Prefer the Present, and When the Present Is Uncertain, People Prefer the Future

2016· article· en· W2188657252 on OpenAlex
David J. Hardisty, Jeffrey Pfeffer

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

VenueManagement Science · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRisk-seekingIntertemporal choiceEconomicsUncertainty avoidanceValue (mathematics)Prospect theoryRelation (database)PsychologyMicroeconomicsSocial psychologyComputer scienceIndividualism

Abstract

fetched live from OpenAlex

Three studies explored the effects of uncertainty on people’s time preferences for financial gains and losses. In general, individuals seek to avoid uncertainty in situations of intertemporal choice. While holding the expected value of payouts constant, participants preferred immediate gains and losses if the future was uncertain, and preferred future gains and losses if the present was uncertain. This pattern of preferences is incompatible with current models of intertemporal choice, in which people should consistently prefer to have gains now and losses later. This pattern of uncertainty avoidance is also not explained by prospect theory models, which predict risk seeking for losses. We discuss these findings in relation to previous literature. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2015.2349 . This paper was accepted by Yuval Rottenstreich, judgment and decision making.

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)0.010
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Open science, 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0100.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.339
Teacher spread0.280 · 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