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Record W2335717768 · doi:10.2190/ic.31.1-2.j

The Depiction of Wheels by Blind Children: Preliminary Studies on Pictorial Metaphors, Language, and Embodied Imagery

2011· article· en· W2335717768 on OpenAlexaff
Maribel Tercedor Sánchez, Pamela Faber, Amedeo D’Angiulli

Bibliographic record

VenueImagination Cognition and Personality · 2011
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsCarleton University
Fundersnot available
KeywordsEmbodied cognitionPsychologyIntrospectionPerceptionMental imageMetaphorSituatedPerspective (graphical)DepictionCognitive psychologyCommunicationLinguisticsCognitive scienceComputer scienceArtificial intelligenceCognition

Abstract

fetched live from OpenAlex

Blind (and visually impaired) children make use of perceptual cues from multimodal sensory input of known objects when they draw. In this study, we examined drawings of spinning wheels made by 12-year-old congenitally blind children. The drawings can be analyzed in terms of metaphoric and metonymic mappings from perceptual cues of different objects. Just as metaphoric language is understood through embodiment, the drawings are made through embodiment or perceptual symbolic simulations that have their parallel in language. We considered the relation between metaphor in haptic drawings and language from the perspective of situated simulation in which imagery, motion, and introspection play a crucial role in the shaping of concepts. Reference corpora offer evidence of the verbal correlates of such simulations in English and Spanish.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.332
Teacher spread0.290 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2011
Admission routes1
Has abstractyes

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