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Record W2623474886

Haptic Pictures, Blindness, and Tactile Beliefs: Preliminary Analysis of a Case-Study

2006· article· en· W2623474886 on OpenAlexaff
Amedeo D’Angiulli

Bibliographic record

VenueeScholarship (California Digital Library) · 2006
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsHaptic technologyPsychologyPerceptionHaptic perceptionSet (abstract data type)Representation (politics)Identification (biology)Meaning (existential)Cognitive psychologyBlindnessSimilarity (geometry)Perspective (graphical)Artificial intelligenceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Research on the identification of raised-outline drawings (haptic pictures) indicates that blind and sighted individuals process pictorial information similarly.To explain this similarity, the partial overlap hypothesis argues that pictorial representation is constrained by principles grounded on objective shape perception that are shared by vision and haptics.In contrast, the tactile beliefs hypothesis maintains that such similarity is not given by our tactile experience, but by indirect, meaning-based representation of such experience.In this case-study, a 13-year old child born completely blind was invited to explore and identify a set of haptic pictures.He then was invited to explain, verbally and/or by drawing, why he believed that the referents he suggested identified accurately the depicted objects.Identification and recognition memory of haptic pictures were interrelated, but unrelated to tactile beliefs.The findings support the partial overlap hypothesis.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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 designCase report
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

Citations1
Published2006
Admission routes1
Has abstractyes

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