Bibliographic record
Abstract
Memory for paired-associate words is facilitated by interim testing relative to restudy. According to the mediator effectiveness hypothesis, the benefit of retrieval practice is a consequence of the activation of a mediator word linking the cue and target. Evidence for the activation of cue-related mediators stems from the finding that mediators are more effective at prompting recall of target words than are words not associated with the original cue, a pattern that is larger following testing than restudy. The benefit of testing for the unstudied cues at the final test is referred to as transfer of test-enhanced learning. One goal of the current study was to examine whether the activation of mediators leads to the recall of targets indirectly via the original cues in a process known as backward chaining. We indexed backward chaining with the probability of incorrectly recalling a trial-specific original cue in place of a target. The second goal was to explore whether testing would yield a transfer effect for cues associated with target words. In four experiments, following an initial study of weakly related word pairs (e.g., Mother-CHILD), participants either restudied the pairs or attempted to recall the target given the original cue (e.g., Mother). On a final cued-recall test, participants were presented with unstudied cues that were related to either the original cue (semantic mediators, e.g., Father) or the target (target-related cues, e.g., Baby). The type of new cue presented on the final test was varied either between subjects (Experiment 1) or mixed within a list (Experiments 2, 3, and 4). Mixing mediators and target-related cues reduced the transfer of test-enhanced learning and increased the likelihood of recalling the original cues when shown a mediator. These results challenge the assumptions of the mediator effectiveness 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".