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Development of Early Handedness, Manual Specialization, and Hemispheric Specialization

2020· other· en· W2999134651 on OpenAlexaff
Gerald Young

Bibliographic record

VenueThe Encyclopedia of Child and Adolescent Development · 2020
Typeother
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsYork University
Fundersnot available
KeywordsLateralityLateralization of brain functionPsychologyCognitive psychologyFunctional specializationEquipotentialRight hemisphereDevelopmental psychologyMotor skillNeuroscience

Abstract

fetched live from OpenAlex

The development of handedness is related to the development of specialized manual function but follows its own developmental trajectory. Specialized lateralized hand function is referred to as manual specialization and is considered a reflection of underlying hemispheric specialization—for example, in terms of the left hemisphere's superior fine motor and language skills and the right hemisphere's superior spatial skills. The two major models used to explain laterality development concern an early equipotential and then a progressive lateralization of development versus an invariant model—for example, in which the two hemispheres exhibit from early in life the characteristics of adult hemispheric specialization. This entry critically examines the development of handedness, manual specialization, and hemispheric specialization, and, novel to the literature, shows that the equipotential and invariant models are not contradictory. It examines research for both lateralized behavior and brain structure and function from one age period to the next (prenatal to preschool). The research points to connectivity and network models as new ways of explaining left–right differences in brain and behavior, which tie into a proposed activation–inhibition coordination model. The origins of laterality in behavior and brain are shown to lie in biological and environmental influences, including genetically and culturally.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.519
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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