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Record W4389204500 · doi:10.1038/s41598-023-48133-1

Short-term evidence of partner-induced performance biases in simultaneous and alternating dyad practice in golf

2023· article· en· W4389204500 on OpenAlexafffund
Matthew W. Scott, Jonathan Howard, April Karlinsky, Aneesha Mehta, Timothy N. Welsh, Nicola J. Hodges

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsDyadContext (archaeology)HarmPsychologyMotor learningRepresentation (politics)Social psychologyCognitive psychologyPolitical science

Abstract

fetched live from OpenAlex

Actions in social settings are often adapted based on co-actors. This adaptation can occur because one actor "co-represents" the actions and plans of another. Co-representation can result in motor contagion errors, whereby another's actions unintentionally interfere with (negatively impact) the actor. In sports, practice often takes place simultaneously or alternating with a partner. Co-representation of another's task could either harm or benefit skill retention and transfer, with benefits due to variable experiences and effortful processes in practice. Here, dyad groups that either alternated or simultaneously practiced golf putting to different (near vs. far) targets were compared to alone groups (n = 30/group). We focused on errors in distance from the target and expected overshooting for near-target partners paired with far-target partners (and undershooting for far-target partners paired with near-target partners), when compared to alone groups. There was evidence of co-representation for near-target partners paired with far-target partners. We also saw trial-to-trial error-based adjustments based on a partner's outcome in alternating dyads. Despite differences in practice between dyad and alone groups, these did not lead to costs or benefits at retention or transfer. We conclude that the social-context of motor learning impacts behaviours of co-actors, but not to the detriment of overall learning.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.130
GPT teacher head0.408
Teacher spread0.278 · 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 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

Citations5
Published2023
Admission routes2
Has abstractyes

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