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Record W2103610395 · doi:10.6000/1927-5129.2014.10.42

Attentional Strategies During Rowing

2014· article· en· W2103610395 on OpenAlexvenueno aff
Daniel P. Longman, Jasmin Hutchinson, Jay T. Stock, Jonathan C. K. Wells

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2014
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsRowingPsychologyAssociation (psychology)Task (project management)Associative propertyAttentional biasSelective attentionCognitive psychologyCognitionNeuroscienceMathematics

Abstract

fetched live from OpenAlex

This investigation explored the relationship between task intensity, competitive setting, and attentional strategy in collegiate rowers. Here, the associative-dissociative dimension of attentional focus is considered. Associative thoughts are task-related, whereas dissociative thoughts are not. Previous work has linked associative strategies with higher level performance, and higher intensities of exercise (i.e. those which exceed the ventilatory threshold). Male and female collegiate rowers (N = 298) completed three training sessions (one each at low, moderate, and high intensity) and two races (short and long distance). Results revealed that the higher the training intensity, the greater the degree of association. A greater degree of association was also observed in competition as opposed to training, and in short distance versus long distance races. There was no gender difference in attentional strategy. Finally, it was shown that the variation in attentional strategy was inversely proportional to exercise intensity. These findings support previous work examining the effect of task intensity on attentional focus [1], in a field based setting. Furthermore, new insight is offered regarding how competition interacts with intensity in this relationship.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score1.000

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.320
Teacher spread0.294 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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