I before U: Temporal order judgements reveal bias for self-owned objects
Bibliographic record
Abstract
A multitude of studies demonstrate that self-relevant stimuli influence attention. Self-owned objects are a special class of self-relevant stimuli. If a self-owned object can indeed be characterised as a self-relevant stimulus then, consistent with theoretical predictions, a behavioural effect of ownership on attention should be present. To test this prediction, a task was selected that is known to be particularly sensitive measure of the prioritisation of visual information: the temporal order judgement. Participants completed temporal order judgements with pictures of "own" and "experimenter" owned objects (mugs) presented on either side of a central fixation cross. There was a variable onset delay between each picture, ranging between 0 ms and 105 ms, and participants were asked to indicate which mug appeared first. The results indicated a reliable change in the point of subjective simultaneity (PSS) in favour of their own mug. Such a change in the PSS was not observed for two groups of participants who were exposed to a mug but did not keep the mug. A further experiment indicated that the source of the bias in PSS was more consistent with a criterion shift or top-down attentional prioritisation rather than a perceptual bias. These findings suggest that ownership, beyond mere-touch, mere-choice, or familiarity, leads to prioritised processing and responses, but the mechanism underlying the effect is not likely to be perceptual in nature.
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".