Semantic Relatedness Effects in Serial Recall But Not in Serial Reconstruction of Order
Bibliographic record
Abstract
Lists of semantically related words are better recalled than lists of unrelated words on immediate serial recall tests. Prominent explanations for this beneficial effect of semantic relatedness, such as the item/order hypothesis, invoke differential contributions of item and order information and predict that on tests that de-emphasize item information, the effect of semantic relatedness will be abolished. The prediction is hard to assess because previous studies using reconstruction of order tests show conflicting and equivocal results. Three experiments are reported that were designed to minimize problems associated with extant studies and that will allow reassessment of the prediction that semantic relatedness will have no effect on reconstruction of order tests. The experiments replicated the usual beneficial effect of semantic relatedness on memory when the test was serial recall but found no effect when the test was reconstruction of order. These results were observed regardless of whether semantic relatedness was defined by category membership (Experiment 1), association (Experiment 2), or meaning (Experiment 3). These results clarify earlier results in the literature and confirm a strong prediction of the item/order hypothesis.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".