A test of the symbol interdependency hypothesis with both concrete and abstract stimuli
Bibliographic record
Abstract
In Experiment 1, the symbol interdependency hypothesis was tested with both concrete and abstract stimuli.Symbolic (i.e., semantic neighbourhood distance) and embodied (i.e., iconicity) factors were manipulated in two tasks-one that tapped symbolic relations (i.e., semantic relatedness judgment) and another that tapped embodied relations (i.e., iconicity judgment).Results supported the symbol interdependency hypothesis in that the symbolic factor was recruited for the semantic relatedness task and the embodied factor was recruited for the iconicity task.Across tasks, and especially in the iconicity task, abstract stimuli resulted in shorter RTs.This finding was in contrast to the concreteness effect where concrete words result in shorter RTs.Experiment 2 followed up on this finding by replicating the iconicity task from Experiment 1 in an ERP paradigm.Behavioural results continued to show a reverse concreteness effect with shorter RTs for abstract stimuli.However, ERP results paralleled the N400 and anterior N700 concreteness effects found in the literature, with more negative amplitudes for concrete stimuli. Symbolic theoryLanguage comprehension has been explained through symbolic-also referred to as linguistic, distributional, computational, or amodal-theories [1].We are not considering symbolic approaches to cognition in general, but rather, we are using a constrained definition of symbolic theory here to discuss a particular type of symbolic theory relevant to the semantic
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".