Hierarchical organization influences on object- and location-based inhibition of return
Bibliographic record
Abstract
The Inhibition of Return (IOR; Posner et al, 1988) effect reflects a mechanism that biases attention from re-examining previously attended regions (Posner & Cohen, 1984) or objects (Jordan & Tipper, 1998; Tipper, Jordan & Weaver, 1999). A previously attended object, if moved to a novel location, also carries with it an inhibitory ‘tag’. Object-based IOR is carried both by outlined-objects (Jordan & Tipper, 1998) or surfaces defined by a field of dots, even when superimposed upon another surface (Johnson, Fallah, & Jordan, VSS 2008). We probed the level of hierarchical organization that maintains object-based IOR as the object moves across the visual field. A modified version of the cueing paradigm, which dissociates object- and location-based IOR effects was used (Tipper et al, 1999). In the present study, we investigated whether object-based IOR is mediated at a local (individual dots) or global (surface) stage of object processing. The display consisted of a single surface of dots in the shape of an annulus. The surface was visible through three apertures in an invisible occluder. While controlling for perceptual complexity, in one display condition the dots rotated (local), while in the other display condition the aperture rotated over the static surface (global). The location-based IOR effect was significantly larger in the local condition (p = .003). Despite manipulating the hierarchical organization of the objects in the display, remarkably there was no difference in the object-based IOR effects observed in the two conditions (p = .557). These results are discussed in light of previous research and current models of spatial and object-based attention.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".