Imagery as a Skill: Longitudinal Analysis of Changes in Motivational Imagery
Bibliographic record
Abstract
Imagery intervention research indicates that athletes improve their imagery skill through practice. As a skill, imagery is expected to improve over time only if athletes increase their use of imagery (i.e., engage in imagery practice). Forty-four track-and-field athletes striving for selection to national games completed the Sport Imagery Questionnaire to assess imagery use and the Motivational Imagery Ability Measure to assess imagery ability. The athletes completed the measures three times within 13 months prior to the games. Although cognitive general imagery use increased over time, paired t-tests indicated that there were no other significant changes across the functions of imagery use. For motivational imagery ability, there were minimal changes from Time 1 to Time 3 indicating the athletes’ motivational imagery ability remained relatively stable. These results add support for targeted imagery interventions as athletes do not spontaneously or independently begin to increase their use of imagery; athletes need purposeful interventions to realize improvements in imagery skills.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".