On the relationship between recognition speed and accuracy for words rehearsed via rote versus elaborative rehearsal.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tacit within both lay and cognitive conceptualizations of learning is the notion that those conditions of learning that foster "good" retention do so by increasing both the probability and the speed of access to the relevant information. In 3 experiments, time pressure during recognition is shown to decrease accessibility more for words learned via elaborative rehearsal than for words learned via rote rehearsal, despite the fact that elaborative rehearsal is a more efficacious learning strategy as measured by the probability of access. In Experiment 1, participants learned each word using both types of rehearsal, and the results show that access to the products of elaborative rehearsal is more compromised by time pressure than is access to the products of rote rehearsal. The results of Experiment 2, in which each word was learned via either pure rote or pure elaborative rehearsal, exhibit the same pattern. Experiment 3, in which the authors used the response-signal procedure, provides evidence that this difference in accessibility owes not to differences in the rate of access to the 2 types of traces, but rather to the higher asymptotic level of stored information for words learned via elaborative rehearsal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it