Effects of Neighborhood Density on Adult Word Repetition
Bibliographic record
Abstract
Presumable lexical competition has been found to result in higher perceptual accuracy for words with few versus many neighbors. Previous studies have typically only analyzed the lexical-semantic level, however. In order to also explore the possibility of phonological effects, a word repetition task was administered to 46 typical adults in which 80 stimuli differed only in neighborhood density. In contrast to previous studies, verbal responses were elicited in order to analyze productions holistically and segmentally at the phonological level. An additional error analysis examined differences in neighborhood density between target words and substitutions. Findings revealed that words with more neighbors facilitated recognition, and were more accurately repeated than those with fewer neighbors. When a target word was misperceived, its substitution tended to be higher in neighborhood density, unrelated to word frequency. In order to interpret these results, an account of lexical competition is re-visited with consideration of characteristics of the lexicon discovered using graph theory (Vitevitch, 2008).
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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 | 0.001 | 0.007 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".