This time it’s personal: the memory benefit of hearing oneself
Bibliographic record
Abstract
The production effect is the memory advantage of saying words aloud over simply reading them silently. It has been hypothesised that this advantage stems from production featuring distinctive information that stands out at study relative to reading silently. MacLeod (2011) (I said, you said: The production effect gets personal. Psychonomic Bulletin & Review, 18, 1197-1202. doi: 10.3758/s13423-011-0168-8 ) found superior memory for reading aloud oneself vs. hearing another person read aloud, which suggests that motor information (speaking), self-referential information (i.e., "I said it"), or both contribute to the production effect. In the present experiment, we dissociated the influence on memory of these two components by including a study condition in which participants heard themselves read words aloud (recorded earlier) - a first for production effect research - along with the more typical study conditions of reading aloud, hearing someone else speak, and reading silently. There was a gradient of memory across these four conditions, with hearing oneself lying between speaking and hearing someone else speak. These results imply that oral production is beneficial because it entails two distinctive components: a motor (speech) act and a unique, self-referential auditory input.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| 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".