Performance appraisal of coaches: Acomparative study
Bibliographic record
Abstract
Within the sport environment, the performance appraisal of coaches continues to be an issue. The performance appraisal of coaches is critical to sport organizations since major decisions like rewarding or terminating coaches is based on it. The purpose of this study was to examine whether any differences exist with regard to the importance attached to thefacets identified by MacLean and Chelladurai (1995) between South African sport coaches and administrators and Canadian sport coaches andadministrators. A secondary purpose was to examine whether there were any differences between coaches and administrators overall. The third purpose was to examine whether there was any interaction between country and administrators or coaches in terms of the predetermined facets. Data was collected using the Scale of Coaching Performance (SCP) anddemographics developed by MacLean and Chelladurai (1995). A purposive sample of 300 sport coaches and 150 administrators from sportorganizations in South Africa comprised the participants in this study while 532 coaches and 87 administrators formed the Canadian sample for thestudy. A reliability test was conducted on six pre-determined facets of performance appraisal. A multivariate analysis of variance (MANOVA) wasconducted to examine differences in the importance attached to the various facets by coaches and administrators in the different countries. The results indicated that overall there were significant differences with regard to team products, personal products, indirect task behaviours and public relations behaviours. The study found that common ground seems to exist between the two countries regarding the appraisal of coaches. It also found that the views of administrators and coaches regarding the appraisalof coaches do not always coincide.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".