Individual differences in cognitive map accuracy: Investigating the role of landmark familiarity.
Bibliographic record
Abstract
Broad individual differences exist in the ability to create a cognitive map of a new environment. The current studies investigated whether familiarizing participants with to-be-learned target landmarks (Experiment 1) or target landmarks plus the order they would be encountered along routes (Experiment 2) before exploring the Silcton virtual environment would increase performance on tasks assaying spatial memory of Silcton. Participants in both experiments were randomly assigned to be pre-exposed either to information about target landmarks in Silcton or control landmarks on the university campus. In both experiments, participants explored Silcton via four prescribed routes and then performed a direction estimation task and a map building task based on memory for the locations of the target landmarks. In addition, participants completed the Spatial Orientation Test of perspective-taking. Pre-exposure to Silcton landmarks versus control landmarks did not affect scores on Silcton-based tasks in either experiment. Some sex differences in direction estimation were observed in Experiment 1 but not Experiment 2. While facilitating familiarity with landmarks did not improve cognitive map accuracy, both sex and perspective taking ability were found to contribute to individual differences in the ability to create a cognitive map. (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 | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".