On the Strength of Connections Between Localist Mental Modules as a Source of Frequency-of-Occurrence Effects
Bibliographic record
Abstract
Frequency-of-occurrence effects (e.g., effects of word frequency or familiarity) are widely thought to arise through differences in resting levels of activation in localist input-output modules. A different account posits that these effects at least partially reflect the strength of connections between various localist modules. Given that Arabic numerals appear more frequently than their alphabetic counterparts, we contrasted reaction times to stimuli in both formats in a naming/reading-aloud task and a parity-judgment task. The script effect (the difference between reaction times to Arabic and to alphabetic formats) was large in the parity-judgment task but absent in the naming/reading-aloud task. This script-by-task interaction follows naturally from the idea that at least part of the effect of frequency of occurrence of a printed word or digit (and other instances of familiarity) resides in the strength of connections between specialized localist input-output modules and a localist semantic module. This conclusion is likely applicable across a variety of domains.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".