Enhancing the Collective Efficacy of a Soccer Team through Motivational General-Mastery Imagery
Bibliographic record
Abstract
The purpose of this study was to implement a motivational general-mastery imagery intervention in order to increase a soccer team's collective efficacy. The participants were 14 female members of a competitive traveling soccer club ( M = 11.47 years, SD = .74). All athletes were placed into one of three groups based on playing position: forwards, midfielders, or defense/goal keeper. A staggered multiple baseline design across groups was employed to evaluate the imagery intervention. Collective efficacy data for training and competition were collected once a week for 13 weeks. The imagery intervention began at weeks 4, 7, and 10 for the forwards, midfielders and defense/goal keeper, respectively. Results from visual inspection as well as Binomial tests revealed athletes' collective efficacy increased with the implementation of the motivational general-mastery imagery intervention for both training and competition for two of the three groups. In order to investigate the athlete's individualized imagery use, an imagery assessment questionnaire was administered. The results showed that the athletes used imagery on almost a daily basis. As well, the athletes had a very positive reaction to the imagery training.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".