Consistency just feels right: Procedural fluency increases confidence in performance.
Bibliographic record
Abstract
Incidental features of a stimulus can increase how easily it is processed, which can then increase confidence in task performance. Here, we examine the impact of fluency stemming from procedural features embedded in a task rather than in the features of a stimulus. We propose that manipulating the consistency of procedural features over a series of stimuli can produce procedural fluency, a metacognitive sense of ease in processing that can inflate confidence without boosting accuracy. That is, even superficial consistency within a task can lead people to inaccurately believe they are performing better. As with fluency derived from features of individual stimuli, drawing attention to procedural consistency leads people to discount it, attenuating its impact on confidence. Further, the influence of procedural fluency on confidence relies on individuals' naïve theories about what fluency signals about their performance. Accordingly, manipulating these naïve theories mitigates the effects of procedural fluency on confidence. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".