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Record W3092387920 · doi:10.1123/iscj.2020-0001

Coaches’ Use of Positive Tactile Communication in Collegiate Basketball

2020· article· en· W3092387920 on OpenAlexaff
Inge Milius, Wade Gilbert, Danielle Alexander, Gordon A. Bloom

Bibliographic record

VenueInternational Sport Coaching Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsMcGill University
Fundersnot available
KeywordsCoachingBasketballPsychologyApplied psychologyAthletesPerceptionData collectionQualitative propertyComputer sciencePhysical therapy

Abstract

fetched live from OpenAlex

There is a growing body of research on positive tactile communication and its impact on athlete performance and team dynamics. The purpose of the present study was to examine the profile and perceived impact of positive tactile communication as a coaching strategy in a high-performance team sport setting. Participants were members of a successful American collegiate women’s basketball team comprising the head coach, associate head coach, and 16 student-athletes. Methods of data collection included systematic observation and focus groups. Positive tactile communication was perceived to be an effective coaching strategy for enhancing relationships and athlete performance. To our knowledge, this is the first study to include both quantitative and qualitative data from multiple coaches on the same team, as well as athlete perceptions of coaches’ strategic use of positive tactile communication.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.061
GPT teacher head0.335
Teacher spread0.274 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

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