Effects of perspective and belief on analytic reasoning in a scientific reasoning task
Bibliographic record
Abstract
The purpose of these studies was to test the hypothesis that changing perspectives from one's own to another's promotes the engagement of analytic processing and, in turn, reduces the impact of beliefs. In two experiments participants evaluated research vignettes containing belief-consistent and belief-inconsistent conclusions, and indicated whether the data supported a correlation between two variables. Consistent with our hypothesis, the tendency to endorse correlations consistent with prior belief was reduced when participants evaluated the data from the researcher's perspective relative to their own. We also administered the Actively Open Minded Thinking (AOT) scale (Stanovich & West, 2007, 2008), which did not predict belief effects on our task. We did however observe that the AOT was reliably associated with different response strategies: high AOT scorers were more inclined to choose ambiguous response options, such as “no conclusion is warranted”, whereas low scorers evinced a preference for more determinate options (e.g., there is no relationship between the two variables). We interpret our findings in the context of dual process theories of reasoning and from a Bayesian perspective.
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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 | 0.007 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".