Symbol superiority: Why $ is better remembered than ‘dollar’
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
Memory is often superior for pictures relative to words. Dual-coding theory (Paivio, 1969) proposes that this is because pictures lead to imagery plus verbal labelling, taking advantage of two codes, whereas words provide only a verbal representation in memory. We investigated whether common symbols (e.g., !@#$%&) are processed with dual codes, like pictures, or a single code, like words. Participants’ memory were tested for symbols or words (e.g., $ or ‘dollar’). We predicted that symbols are processed using imagery, much like pictures, and as a result memory for symbols should be superior to words. Our prediction was supported across four experiments: Symbols were consistently better remembered than words, regardless of setting, design, or retrieval test type. In a fifth experiment, memory for symbols was driven in-part by participants' familiarity with the stimuli as well as the highly memorable visual properties that symbols possess (as estimated by the ResMem neural network). These findings are consistent with the idea that symbols benefit memory by eliciting distinct representations at encoding.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it