Doing things efficiently: Testing an account of why simple explanations are satisfying
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.
Bibliographic record
Abstract
• We examined why people prefer simple explanations. • We suggest the preference arises because people value completing goals efficiently. • Participants evaluated the appeal of explanations and causal processes. • Participants generally preferred simple methods as both explanations and processes. • Statistical information diminished and reversed this preference in parallel for both judgments. People often find simple explanations more satisfying than complex ones. Across seven preregistered experiments, we provide evidence that this simplicity preference is not specific to explanations and may instead arises from a broader tendency to prefer completing goals in efficient ways. In each experiment, participants (total N =2820) learned of simple and complex methods for producing an outcome, and judged which was more appealing—either as an explanation why the outcome happened, or as a process for producing it. Participants showed similar preferences across judgments. They preferred simple methods as explanations and processes in tasks with no statistical information about the reliability or pervasiveness of causal elements. But when this statistical information was provided, preferences for simple causes often diminished and reversed in both kinds of judgments. Together, these findings suggest that people may assess explanations much in the same ways they assess methods for completing goals, and that both kinds of judgments depend on the same cognitive mechanisms.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it