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Record W6999936365

Does your dominant hand become less dominant with time? The effects of aging and task complexity on hand selection

2012· article· en· W6999936365 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsLateralityDominance (genetics)Hand preferenceTask (project management)Lateralization of brain functionAssociation (psychology)Motor skill
DOInot available

Abstract

fetched live from OpenAlex

The current study examines the development of laterality throughout the lifespan, with an emphasis on aging beyond adulthood. The experimental paradigm proposes a measurement tool designed to determine the effects of task complexity, a currently misunderstood factor in hand selection. A cross-sectional sample of 60 participants (10 between 3-4 years, 10 between 10-14 years, 20 between 18-25 years, and 20 over 65 years) were asked to complete the Waterloo Handedness Questionnaire, Tapley-Bryden Dot Marking Task, and a newly created Task Complexity Gradient. This novel task required participants to reach into both ipsilateral and contralateral peripersonal space in order to complete a series of increasingly complex tasks. Although the development of lateralization is well documented throughout childhood and into adulthood, beyond adulthood the relevant literature is contradictory. Prior work has suggested an increase in motor dominance with age, while more recent studies have proposed an approach to ambidexterity. Contrary to both these suggestions, statistical analysis revealed neither an increase nor decrease in laterality with age, but that motor dominance remains consistent throughout later adulthood. The implications of these findings are discussed in terms of motor dominance throughout the lifespan and the task factors that determine hand selection.Acknowledgments: The research described here was funded by a grant from the Natural Sciences and Engineering Research Council of Canada (NSERC) to Pamela J. Bryden, and a grant from the Faculty of Science Students Association (FOSSA) to Spencer E. Gooderham. Further recognition must be extended to Schlegel Villages and the Research Institute for Aging for their continued support.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.025
GPT teacher head0.268
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2012
Admission routes2
Has abstractyes

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