Bibliographic record
Abstract
The motivational functions of imagery include images of feeling confident, in control, and mentally tough (Hall et al., 1998). Despite the important contribution of mental toughness to athletic performance (Jones et al., 2007), little quantitative research has been devoted to examining this construct, or to developing strategies to enhance or maintain mental toughness. The present study investigated the relationship between imagery use and mental toughness. Participants included 151 varsity athletes (Mage = 20.70 ▒ 1.84). Imagery use was assessed using the Sport Imagery Questionnaire (Hall et al., 1998) and mental toughness with the Mental Toughness 48 Inventory (Clough et al., 2002). Hierarchical multiple regression analyses revealed that the motivational functions of imagery significantly predicted mental toughness, while the cognitive functions contributed minimally to the variance in mental toughness. Findings from the present study suggest that imagery use may be an effective strategy for developing or enhancing mental toughness in athletes.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".