Developing global spatial representations through across-boundary navigation.
Bibliographic record
Abstract
This study investigated the extent to which people can develop a global representation of local environments through across-boundary navigation. Participants learned objects' locations in two misaligned rectangular rooms in an immersive virtual environment. After learning, they adopted a local view in one room and judged directions of objects within the room; the views in two consecutive trials were from different rooms and locally or globally consistent (priming task). In some experiments, participants learned locations of five buildings before learning the objects in the rooms. In testing, after the priming task, they pointed to the buildings while adopting local views inside the rooms (across-boundary pointing task). Participants' estimated global headings were calculated from their pointing responses. The results showed that the priming effect from the globally consistent views occurred when participants learned the buildings and then locomoted between the rooms through a simple path. Consistent with the global priming effect, the means of participants' estimated global headings were accurate. In contrast, there was only the priming effect from the locally consistent views when participants did not learn the buildings before learning the objects inside the rooms or when participants were teleported between the rooms after learning the buildings. These results suggest that people can develop global representations of local environments through across-boundary navigation while traveling a simple path, provided that there are prior global representations. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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".