Creating a recollection-based memory through drawing.
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
Drawing a picture of to-be-remembered information substantially boosts memory performance in free-recall tasks. In the current work, we sought to test the notion that drawing confers its benefit to memory performance by creating a detailed recollection of the encoding context. In Experiments 1 and 2, we demonstrated that for both pictures and words, items that were drawn by the participant at encoding were better recognized in a later test than were words that were written out. Moreover, participants' source memory (in this experiment, correct identification of whether the word was drawn or written) was superior for items drawn relative to written at encoding. In Experiments 3A and 3B, we used a remember-know paradigm to demonstrate again that drawn words were better recognized than written words, and further showed that this effect was driven by a greater proportion of recollection-, rather than familiarity-based responses. Lastly, in Experiment 4 we implemented a response deadline procedure, and showed that when recognition responses were speeded, thereby reducing participants' capacity for recollection, the benefit of drawing was substantially smaller. Taken together, our findings converge on the idea that drawing improves memory as a result of providing vivid contextual information which can be later called upon to aid retrieval. (PsycINFO Database Record
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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