Comparison of the on-hand and off-hand straight spikes in volleyball / by Brian Luk-Ming Kan. --
Bibliographic record
Abstract
The purpose of this study was twofold: 1) to examine the differences \nbetween the on-hand side and off-hand side spikes in volleyball in terms \nof velocity and accuracy, and 2) to evaluate the relationship of the \nangle of projection with velocity in each spike. The subjects (N=12) \nwere members of 1979-80 University of Alberta Volleyball Team. \nThe research design employed a repeated measures technique with \ntwo variables, the on-hand and off-hand spikes. Subjects were required \nto perform 20 straight spikes for each technique. The velocity and \nthe angle of projection data for each trial were obtained by cinematographical analysis. Accuracy scores were collected by direct recording after each trial. \nA correlated t test was used to determine the differences in \nvelocity and accuracy between the on-hand and the off-hand spikes. \nA Pearson Product-moment Correlation Coefficient was used to assess \nthe relationship between the velocity and the angle of projection of \neach spiking technique for each subject. A further correlated t test \nwas used to determine differences in that relationship between the \non-hand and off-hand spikes. \nThe results indicated that the differences between the on-hand and \noff-hand spikes, in terms of velocity and accuracy, were significant \n(P < .05). There was no relationship between the velocity and the angle of projection for the on-hand spike but a low significant relationship \nwas observed for the off-hand spike. The difference in relationship of \nvelocity and angle of projection between both spiking techniques was not \nsignificant. Several recommendations for future researches in this area \nwere offered.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".