Familiarity, but not recollection, supports the between-subject production effect in recognition memory.
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
Five experiments explored the basis of the between-subjects production effect in recognition memory as represented by differences in the recollection and familiarity of produced (read aloud) and nonproduced (read silently) words. Using remember-know judgments (Experiment 1b) and a dual-process signal-detection approach applied to confidence ratings (Experiments 2b and 3), we observed that production influences familiarity but not recollection when manipulated between-subjects. This is in contrast to within-subject designs, which reveal a clear effect of production on both recollection and familiarity (Experiments 1a and 2a). Our findings resolve contention concerning apparent design effects: Whereas the within-subject production effect is subserved by separable recollective- and familiarity-based components, the between-subjects production effect is subserved by the familiarity-based component alone. Our findings support a role for the relative distinctiveness of production as a means of guiding recognition judgments (at least when manipulated within-subjects), but we also propose that production influences the strength of produced items, explaining the persistence of the effect in between-subjects designs. (PsycINFO Database Record
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it