Bibliographic record
Abstract
This paper examines decision-making under uncertainty in both timing and outcomes. We introduce a novel type of lottery, the ``two stage compound time-lottery,'' in which the first stage determines the timing and the second stage determines the outcome. Two core axioms of expected utility (EU)—independence and reduction of compound lotteries—are extended to this framework. Building on rank dependent utility, we formulate three more flexible non-EU theories by relaxing one axiom while retaining the other. Recursive Rank Dependent Utility (RRDU) is derived from independence, while Intertemporal Certainty Equivalents (ICE) and Rank Dependent Utility on Discounted Payments (RDUDP) are derived from reduction. These theories exhibit desirable properties: they are monotonic with respect to two stage stochastic dominance, an extension of stochastic dominance to our framework, and they can account for behavioral evidence showing a positive correlation between risk attitudes toward timing and outcomes. To compare the predictive performance of the alternative theories against conventional discounted expected utility (DEU), we conducted a choice experiment involving structurally distinct lotteries, designed so that the theories yield different predictions about their relative attractiveness. The results show that approximately two-thirds of subjects’ choices are consistent with RRDU and one-third with RDUDP, while DEU and ICE together account for only 7% of subjects. These findings suggest that DEU and EU-based models imposing both independence and reduction have limited predictive power when both outcome and timing uncertainty are present, whereas the proposed non-EU theories provide a better fit.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".