Source‐monitoring accuracy across repeated tests following directed forgetting
Bibliographic record
Abstract
The repeated recall of items from lists that participants were earlier instructed to either remember or to forget was examined in two experiments. RR participants (those instructed to remember both lists they were presented) tended to recall more List 1 items than FR participants (those instructed to forget the first list and to remember the second list). FR participants recalled more List 2 items than did RR participants, but only when directed to report those items (Experiment 1), not when directed to report items from both lists (Experiment 2). Participants experienced difficulty correctly reporting the list source of items they recalled and incorrect source recall increased across tests, showing hypermnesia. This later result underscores the need for caution when assessing the accuracy of information retrieved from multiple sources across repeated tests. Together, the data patterns provide support for the retrieval dynamics account of hypermnesia, the context-change account of directed forgetting, and limited support for the retrieval inhibition view of directed forgetting.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".