Choice as an engine of analytic thought.
Bibliographic record
Abstract
Choice is a behavioral act that has a variety of well-documented motivational consequences-it fosters independence by allowing people to simultaneously express themselves and influence the environment. Given the link between independence and analytic thinking, the current research tested whether choice also leads people to think in a more analytic rather than holistic manner. Four experiments demonstrate that making choices, recalling choices, and viewing others make choices leads people to think more analytically, as indicated by their attitudes, perceptual judgments, categorization, and patterns of attention allocation. People who made choices scored higher on a subjective self-report measure of analytic cognition compared to whose did not make a choice (pilot study). Using an objective task-based measure, people who recalled choices rather than actions were less influenced by changes in the background when making judgments about focal objects (Experiment 1). People who thought of others' behaviors as choices rather than actions were more likely to group objects based on categories rather than relationships (Experiment 2). People who recalled choices rather than actions subsequently allocated more visual attention to focal objects in a scene (Experiment 3). Together, these experiments demonstrate that choice has important yet previously unexamined consequences for basic psychological processes such as attention and cognition. (PsycINFO Database Record
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".