“Going episodic”: collaborative inhibition and facilitation when long-married couples remember together
Bibliographic record
Abstract
Two complementary approaches to the study of collaborative remembering have produced contrasting results. In the experimental "collaborative recall" approach within cognitive psychology, collaborative remembering typically results in "collaborative inhibition": laboratory groups recall fewer items than their estimated potential. In the cognitive ageing approach, collaborative remembering with a partner or spouse may provide cueing and support to benefit older adults' performance on everyday memory tasks. To combine the value of experimental and cognitive ageing approaches, we tested the effects of collaborative remembering in older, long-married couples who recalled a non-personal word list and a personal semantic list of shared trips. We scored amount recalled as well as the kinds of details remembered. We found evidence for collaborative inhibition across both tasks when scored strictly as number of list items recalled. However, we found collaborative facilitation of specific episodic details on the personal semantic list, details which were not strictly required for the completion of the task. In fact, there was a trade-off between recall of specific episodic details and number of trips recalled during collaboration. We discuss these results in terms of the functions of shared remembering and what constitutes memory success, particularly for intimate groups and for older adults.
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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 | 0.002 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".