The impact of text orientation on form priming effects in four-character Chinese words.
Bibliographic record
Abstract
Does visuospatial orientation influence repetition and transposed character (TC) priming effects in logographic scripts? According to perceptual learning accounts, the nature of orthographic (form) priming effects should be influenced by text orientation (Dehaene, Cohen, Sigman, & Vinckier, 2005; Grainger & Holcomb, 2009). In contrast, Witzel, Qiao, and Forster's (2011) abstract letter unit account argues that the mechanism responsible for such effects acts at a totally abstract orthographic level (i.e., the visuospatial orientation is irrelevant to the nature of the relevant orthographic code). The present experiments expanded this debate beyond alphabetic scripts and the syllabic Kana script used by Witzel et al. to a logographic script (Chinese). Experiment 1 showed masked repetition and TC priming effects with primes and targets presented in both the conventional left-to-right horizontal orientation and the vertical top-to-bottom orientation, replicating Witzel et al. Experiment 2 showed masked repetition and TC priming effects even when both the primes and targets were presented in the right-to-left orientation, a rare but existent text orientation in Chinese. In Experiment 3, the primes, but not the targets, were presented in the right-to-left orientation. Priming effects were again obtained regardless of the fact that the primes and targets appeared in different orientations. Experiment 4, which involved primes and targets presented in a completely novel bottom-to-top orientation, also produced a TC priming effect. These results support abstract letter/character unit accounts of form priming effects while failing to support perceptual learning accounts. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.000 |
| 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) | 0.000 | 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".