Grouping effects in immediate reconstruction of order and the preconditions for long-term learning
Bibliographic record
Abstract
One commonly acknowledged role of working memory is to set up conditions for new learning. Yet, it has long been understood that there is not a perfect correspondence between conditions leading to good immediate recall from working memory and conditions leading to good delayed recall from long-term memory. Here, in six experiments, we investigated the relation between grouping effects in immediate and delayed reconstruction of order for word lists. There has been a striking absence of tests of grouping effects in long-term memory. In the first four experiments, items within groups are presented concurrently, which encourages associations between items in a group. Despite that presumably favourable situation for group learning, in Experiments 1 and 2 we found effects of grouping only in immediate order reconstruction and not in delayed reconstruction. When more processing time was allowed (Experiments 3 and 4), grouping effects in both immediate and delayed order reconstruction were obtained. Experiment 5 showed that, with items presented one at a time, but with roughly the same amount of processing time and spatial separation as the previous two experiments, grouping effects were obtained neither in immediate order reconstruction nor in delayed reconstruction. However, in Experiment 6 with a more salient manipulation of grouping, effects of grouping were obtained in immediate order reconstruction, but not in delayed reconstruction. In sum, we demonstrated for the first time that there are mechanisms of temporal grouping that assist working memory but are relatively ineffective for long-term learning, in contrast to more effective, concurrent presentation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".