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Record W2153653372 · doi:10.1037/a0014171

Synesthesia: A new approach to understanding the development of perception.

2009· review· en· W2153653372 on OpenAlexafffund
Ferrinne Spector, Daphne Maurer

Bibliographic record

VenueDevelopmental Psychology · 2009
Typereview
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSynesthesiaPsychologyPerceptionCognitive psychologySensory systemCrossmodalCognitive scienceDevelopmental psychologyVisual perceptionNeuroscience

Abstract

fetched live from OpenAlex

In this article, the authors introduce a new theoretical framework for understanding intersensory development. Their approach is based upon insights gained from adults who experience synesthesia, in whom sensory stimuli induce extra cross-modal or intramodal percepts. Synesthesia appears to represent one way that typical developmental mechanisms can play out by magnifying connections present in early life that are pruned and/or inhibited during development but persist in muted form in all adults. As such, the study of synesthesia provides valuable insights into the nature of intersensory development. The authors review evidence on the perceptual reality and neural basis of synesthesia, then summarize developmental models and evidence that its underlying mechanisms are universal in adults. They illustrate how evidence for consistent sensory associations in adults leads to predictions about toddlers' perception and present 3 bodies of work that have confirmed those hypotheses. They end by describing novel hypotheses about intersensory development that arise from this framework. Such intersensory associations appear to reflect intrinsic sensory cortical organization that influences the development of perception and of language and that may constrain the learning of environmentally based associations.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.005
Scholarly communication0.0020.005
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.002

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 head0.370
GPT teacher head0.457
Teacher spread0.087 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations171
Published2009
Admission routes2
Has abstractyes

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