Testing the item-order account of design effects using the production effect.
Bibliographic record
Abstract
A number of memory phenomena evident in recall in within-subject, mixed-lists designs are reduced or eliminated in between-subject, pure-list designs. The item-order account (McDaniel & Bugg, 2008) proposes that differential retention of order information might underlie this pattern. According to this account, order information may be encoded when a common form of processing is used alone in a list (e.g., reading), but not when an unusual form of processing is used (e.g., generation) or when a common form and an unusual form are mixed within a list. The production effect--better memory for words said aloud than for words read silently--shows this same design-contingent pattern. In 2 experiments, we investigated whether differential order retention might underlie the production effect. Consistent with the item-order account, we found that retention of order information was better in pure silent lists than in either pure aloud lists or mixed lists, as measured using an order reconstruction test. Moreover, in Experiment 2, order was better preserved in free recall of pure silent lists than of either pure aloud or mixed lists. Thus, production joins the set of tasks identified by McDaniel and Bugg (2008), and our findings suggest a role for order processing in explaining the production effect.
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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 | 0.033 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".