Allocentric Spatial Performance Higher in Early-Blind and Sighted Adults Than in Retinopathy-of-Prematurity Adults
Bibliographic record
Abstract
The question as to whether people totally blind since infancy process allocentric or external spatial information like the sighted has caused considerable debate within the literature. Due to the extreme rarity of the population, researchers have often included individuals with retinopathy of prematurity (RoP--over oxygenation at birth) within the sample. However, RoP is inextricably confounded with prematurity per se. Prematurity, without visual disability, has been associated with spatial processing difficulties. In this experiment, blindfolded sighted participants and two groups of functionally totally blind participants heard text descriptions from a survey (allocentric) or route (egocentric) perspective. One blind group lost their sight due to RoP and a second group before 24 months of age. The accuracy of participants' mental representations derived from the text descriptions was assessed via questions and maps. The RoP participants had lower scores than the sighted and early blind, who performed similarly. In other words, it was not visual impairment alone that resulted in impaired allocentric spatial performance in this task but visual impairment together with RoP. This finding may help explain the contradictions within the existing literature on the role of vision in allocentric spatial processing.
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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 | 0.001 | 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) | 0.005 | 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".