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A COMPARATIVE STUDY OF PSYCHOLOGICAL VARIABLES OF STATE AND NATIONAL LEVEL TENNIS PLAYERS

2024· article· en· W4392401832 on OpenAlexaff
Surender Singh, Karan Singh, Vikram Singh

Bibliographic record

VenueInternational Journal of Research -GRANTHAALAYAH · 2024
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsNiagara College
Fundersnot available
KeywordsPsychologyState (computer science)Applied psychologyAdvertisingSocial psychologyMathematicsBusiness

Abstract

fetched live from OpenAlex

The present study aimed to understand the relationship between mindfulness, mental imagery, and subjective sports performance satisfaction. This study was done on male tennis players aged 18 to 28 years who play competitive tennis at the State and National Levels in India. The tools used to measure the variables were The Mindfulness Attention Awareness Scale (MAAS) by Brown & Ryan (2003), Sports Imagery Ability Questionnaire by Williams & Cumming (2014) and Athlete’s Subjective Performance Scale (ASPS) by Nahum et al. (2016). The results of the study show that the national-level tennis players had better self-reported satisfaction scores than the state-level players. Zero-order correlations showed that there was a statistically significant, moderate, positive correlation between Mindfulness and mental imagery (r(53) = -.304, n = 55, p < .05), indicating that subjective sports performance satisfaction had very little influence in controlling for the relationship between Mindfulness score and mental imagery.

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)0.003
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 score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.286
GPT teacher head0.553
Teacher spread0.267 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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