Encoding Context Determines Risky Choice
Bibliographic record
Abstract
Both memory and choice are influenced by context: Memory is enhanced when encoding and retrieval contexts match, and choice is swayed by available options. Here, we assessed how context influences risky choice in an experience-based task in two main experiments (119 and 98 participants retained, respectively) and two additional experiments reported in the Supplemental Material available online (152 and 106 participants retained, respectively). Within a single session, we created two separate contexts by presenting blocks of trials in distinct backgrounds. Risky choices were context dependent; given the same choice, people chose differently depending on other outcomes experienced in that context. Choices reflected an overweighting of the most extreme outcomes within each local context rather than the global context of all outcomes. When tested in the nontrained context, people chose according to the context at encoding and not retrieval. In subsequent memory tests, people displayed biases specific to distinct contexts: Extreme outcomes from each context were more accessible and judged as more frequent. These results pose a challenge for theories of choice that rely on retrieval as guiding choice.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".