Reading aloud: Does previous trial history modulate the joint effects of stimulus quality and word frequency?
Bibliographic record
Abstract
No one would argue with the proposition that how we process events in the world is strongly affected by our experience. Nonetheless, recent experience (e.g., from the previous trial) is typically not considered in the analysis of timed cognitive performance in the laboratory. Masson and Kliegl (2013) reported that, in the context of the lexical decision task, the nature of the previous trial strongly modulates the joint effects of word frequency and stimulus quality-a joint effect that is widely reported to be additive when averaged over trial history. In particular, their analysis suggests there may be no genuine additivity of these factors. Here we extended this line of investigation by reanalyzing data reported by O'Malley and Besner (2008) in which subjects read words and nonwords aloud, with word frequency and stimulus quality as manipulated factors. These factors are additive on reaction time in the standard analysis of variance. Contrary to Masson and Kliegl's finding for lexical decision, when previous trial history is taken into consideration, these 2 factors still do not interact. This suggests that, at least in the context of reading aloud, previous trial does not modulate how the effects of these 2 factors combine. Some implications are briefly noted.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".