What Makes People Revise Their Beliefs Following Contradictory Anecdotal Evidence?: The Role of Systemic Variability and Direct Experience
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
The extent to which belief revision is affected by systematic variability and direct experience of a conditional (if A then B) relation was examined in two studies. The first used a computer generated apparatus. This presented two rows of 5 objects. Pressing one of the top objects resulted in one of the bottom objects being lit up. The 139 adult participants were given one of two levels of experience (5 or 15 trials) and one of two types of apparatus. One of these was completely uniform, while the other had an element that randomly alternated in its result. Following the testing of the apparatus, participants were asked to rate their certainty of the action of the middle element, which was always uniform (the AB belief). Then they were told of an observation inconsistent with this belief. Participants were then asked whether they considered the AB belief or the anecdotal observation to be more believable. Results showed that increased experience decreased the tendency to reject the AB belief, when the apparatus did not have any randomness. However, the presence of a single element showing random variation in the system strongly increased rejection of this belief. A second study looked at the effect of a single random element on a mechanical system as well as an electronic system using graphical representations. This confirmed the generality of the effect of randomness on belief revision, and provided support for the effects of embedding a belief into a system of relations. These results provide some insight into the complex factors that determine belief revision.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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