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Record W2074556889 · doi:10.1177/0013916506287004

Sex-Specific Relationships Between Route-Learning Strategies and Abilities in a Large-Scale Environment

2006· article· en· W2074556889 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment and Behavior · 2006
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of CalgaryUniversity of AlbertaUniversity of SaskatchewanUniversity of Lethbridge
Fundersnot available
KeywordsLandmarkPsychologyScale (ratio)Cognitive psychologySpatial learningCognitionDevelopmental psychologyArtificial intelligenceComputer scienceGeographyCartography

Abstract

fetched live from OpenAlex

Spatial theories identify three aspects of the environment that are used to various degrees in route-learning tasks; namely, landmarks, routes, and configurations. Although research has demonstrated sex differences in the relative predominance of each aspect in route-learning strategies, it is unclear how these sex differences correspond to route-learning abilities in a large-scale environment. The present experiment addresses this void by examining route-learning abilities in an indoor environment. Participants are taken through an unfamiliar route and instructed to find the point of origin using one of three strategies: (a) direct, (b) retrace, and (c) choice. Results reveal sex differences in route-learning abilities in the direct condition. Furthermore, a landmark-biased strategy is used more by females and is associated with better route-learning abilities. The same relationship is not found in males. These findings suggest that sex-specific patterns of relationships exist between strategy use and route-learning abilities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.197
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it