Self-referential encoding of source information in recollection memory
Bibliographic record
Abstract
Self-referential memory encoding has been previously shown to enhance memory. The self-referential facilitation effect has also been found in source memory (memory with contextual details). In this study, we investigated how subjective recollection interacts with the self-referential effect for source memory. Using a remember/know paradigm, we compared source memory accuracy under self-referential encoding and semantic encoding. Two types of source information were included, a “peripheral” source which was not inherent to the encoding activity, and a source information about the encoding context. SRE benefits on source memory accuracy were observed in recollection for both types of source information, but not in familiarity-based memory. In contrast, for familiarity-based memory, semantic encoding resulted in higher source accuracy for the background source compared to self-referential encoding. These results suggest self-referential encoding creates a richer, more detailed memory trace which can be recollected later on.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 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".