Motivation and its impact on the performance of Special Olympic athletes during the 1.5-mile run
Bibliographic record
Abstract
This research was designed to examine two problems: (a) how the presence of extrinsic motivation affected the performance of two groups of Special Olympic Track athletes on a test of cardiovascular endurance, and (b) assess the athletes' motivational orientation and perceived motivation, and compare these outcomes to their performance on two protocols of the 1.5-mile run. Both of these problems were addressed by using two groups of Track and Field athletes (entitled Medallion and Track) from Manitoba Special Olympics (MSO). Athletes were required to perform two 1.5-mile runs, one with verbal motivation from the coaches and one without. In addition, the athletes training programs were examined to determine if there were any real differences. For this research, Motivational Orientation was determined using the Perceived Competence Scale for Children (Harter, 1982). The Manipulation Check of Perceived Motivation was created to determine the athletes' perceived motivation before and after each 1.5-mile run. Theresults from this research demonstrated that: (a) athletes' performances improved with the presence of extrinsic motivation, (b) there was little difference between the athletes' training programs, (c) motivational orientation did not affect performance, and (d) neither group perceived the effect of motivation any differently than the other. Among others, one conclusion from the research is that extrinsic motivation is needed for a maximal performance, although some athletes do have intrinsic qualities. Previous researchers generally have not illustrated the intrinsic qualities found in athletes with a mental disability.
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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 | 0.001 |
| 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) | 0.001 | 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".