Neighborhood frequency effects in simple and complex span: Do high-frequency neighbors help or hurt?
Bibliographic record
Abstract
A word's orthographic neighborhood is the set of words that differ from the target word by one letter. Both Roodenrys (2009) and Robert et al. (Journal of Psycholinguistic Research, 44, 119-125, 2015) posit that orthographic neighbors are activated when the target word is encountered in tasks such as simple and complex span. The two accounts differ in that the former predicts a beneficial effect of this activation, because it produces feedback activation that helps redintegrate the target word, whereas the latter predicts a detrimental effect, because the need to overcome the greater interference from the larger number of higher-frequency items reduces the processing resources available. Four experiments assess the predictions of these two accounts. Experiments 1 and 2 found a beneficial effect of having a higher- compared with a lower-frequency neighborhood in both a simple and a complex span task. Experiments 3 and 4 found no detrimental effect of having one or more neighbors with higher frequency than the target in both a simple and complex span task. Implications for the two theories are discussed.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".