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Record W2140945121 · doi:10.1111/cogs.12087

Rotating With Rotated Text: A Natural Behavior Approach to Investigating Cognitive Offloading

2013· article· en· W2140945121 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCognitive Science · 2013
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaKillam Trusts
KeywordsEmbodied cognitionCognitionNormalization (sociology)Stimulus (psychology)PerceptionCognitive psychologyComputer sciencePsychologyArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Determining how we use our body to support cognition represents an important part of understanding the embodied and embedded nature of cognition. In the present investigation, we pursue this question in the context of a common perceptual task. Specifically, we report a series of experiments investigating head tilt (i.e., external normalization) as a strategy in letter naming and reading stimuli that are upright or rotated. We demonstrate that the frequency of this natural behavior is modulated by the cost of stimulus rotation on performance. In addition, we demonstrate that external normalization can benefit performance. All of the results are consistent with the notion that external normalization represents a form of cognitive offloading and that effort is an important factor in the decision to adopt an internal or external strategy.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.046
GPT teacher head0.330
Teacher spread0.284 · 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