The Influence of Scene Context on Parafoveal Processing of Objects
Bibliographic record
Abstract
Previous research in reading has shown that information about a word is obtained from the parafovea before it is directly fixated, which speeds the processing of that word once it is subsequently fixated (Rayner, 1975). Further research has shown that contextual constraints (e.g. the predictability of a word) lead to an increase in information acquired from the parafovea (Balota, Rayner & Pollatsek, 1985; McClelland & O’Regan, 1981). Studies have also shown similar effects of contextual constraints on the processing of objects (Biederman, Mezzanotte & Rabinowitz, 1982; Henderson & Hollingworth, 1998). In the present study, we examine whether scene context constrains parafoveal processing of objects prior to fixation. Participants were shown a preview of the target object at either 4° (parafovea) or 10° (periphery) from the point of fixation in either a consistent or inconsistent scene context. The preview could be: (i) identical to the target; (ii) a different category with the same shape; (iii) a different category and different shape; or (iv) a black rectangle control. During the saccade towards the preview object, it changed to the target. In Experiment 1, participants had better performance for identical and similarly-shaped previews, with a stronger benefit for consistent contexts. In Experiment 2, participants had to verify whether the target matched a given object name seen before the trial commenced. Results showed a higher sensitivity (A-prime) for consistent vs. inconsistent contexts. In Experiment 3, participants verified the object name at the end of the trial. The added uncertainty of the target identity led to no difference in sensitivity between context conditions, but did demonstrate a difference in bias (B''D) toward ‘yes’ responses between consistent and inconsistent scene contexts. Across the three experiments, we show that scene context does have a constraining effect on preview processing of objects prior to fixation. Meeting abstract presented at VSS 2013
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".