Subjective experiences of recognizing and not recognizing paintings and words.
Bibliographic record
Abstract
In our prior research, average recognition memory response bias tended to be conservative when stimuli were paintings, whereas bias for common English words tended to be liberal or neutral. Efforts to understand the mechanism(s) underlying this materials-based bias effect (MBBE) have yielded new questions but no definitive answers. Here, we report a set of studies exploring the possibility that participants respond more conservatively to paintings because they expect the novel, visually rich paintings to evoke a strong, detailed memory experience at test, whereas the more familiar, visually similar words are not expected to produce this kind of vivid recollection as often. In three studies using variations of the remember/know procedure, we found that correctly recognized paintings were more often reported as "remembered" than were recognized words. There were also parallel materials-based differences in the reported bases for "new" responses. But we did not observe the expected relationships between response bias and these subjective reports. We discuss the implications of these results for accounts of the MBBE, and the more general issue of the role of stimulus materials in recognition memory response bias. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".