THE PERCEPTUAL COMPLETION PROCESS: EVIDENCE FROM 8-YEAR-OLDS, 11-YEAR-OLDS, AND ADULTS
Bibliographic record
Abstract
Three main theories have been proposed to account for the completion of occluded objects, namely local theories (e.g., Kellman & Shipley, 1991), global theories (e.g., Boselie & Leeuwenberg, 1986), and integrative models of completion (e.g., Sekuler, 1994; van Lier et al., 1994). Here, we investigated age-related changes in the completion of a complex partially occluded object using a prime-matching task. Subjects were shown a prime (global, local, occluded, or no prime) that was followed immediately by two shapes that were judged as being the same or different. In Experiment 1, we tested adults (n = 36/group) at various prime durations (150 - 700 msec) to tap into earlier and later representations of the occluded object. Although the occluded object primed both the global and local shapes at 150 and 500 msec (ps<0.05), only the global shapes were primed at 300 and 700 msec (ps<0.05). Overall, our results are most consistent with integrative models of completion. In Experiment 2, we tested 8-year-olds (n = 20) at a prime duration of 700 msec and 11-year-olds (n = 30/group) at a prime duration of 300 or 700 msec. For 11-year-olds, unlike adults, the occluded object did not significantly prime either the global or local shapes at 300 msec (p>0.50). For both 8- and 11-year-olds, the global, local, and occluded primes did not significantly prime either shape at 700 msec (ps>0.50). Based on the current testing conditions, we found that the perceptual completion process may not be adult-like even at 11 years of age.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".