The Agent's Impatience: A Self–Other Decision Model of Intertemporal Choices
Bibliographic record
Abstract
Intertemporal choices represent one of the most prevalent and fundamental trade-offs in consumer decision making. While prior research on intertemporal choices has focused on choices for oneself, intertemporal choices often involve one individual choosing on behalf of another. How do intertemporal choices made for another person differ from otherwise identical choices made for oneself? This research introduces a self–other decision model that distinguishes reaction utility (derived from interpersonal feedback) from vicarious utility (derived from imagining the recipient's experience). The authors tested model-derived hypotheses in 13 experiments (N = 4,799) involving decisions between peers. Consistent with the proposed role of reaction utility in the model, they find that intertemporal choices made for others are typically more “impatient” than choices for oneself. Moreover, this “agent's impatience” is attenuated when contextual and individual differences weaken the anticipation of interpersonal feedback. Together, the theoretical model and experimental results highlight the rewarding value of interpersonal feedback in self–other decision making, shedding new light on interpersonal consumer choices.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".