History of Sport, Exercise, and Performance Psychology in Southern Africa
Bibliographic record
Abstract
Abstract Since the 1970s, significant growth globally has occurred in the related fields of sport, exercise, and performance psychology. In Southern Africa, however, this growth has occurred unevenly and, other than isolated pockets of interest, there has been little teaching, research, or practice. South Africa is an exception, however, even during the years of apartheid. A number of international sport psychology pioneers in fact visited South Africa during the 1970s on sponsored trips. Virtually all this activity took place in the economically advantaged sectors of the country, and it is only since the end of apartheid in 1994 that applied services have been extended to the economically disadvantaged areas through both government and private funding. The 2010s have also seen a growing awareness in other Southern African countries, which have begun sporadically using (mainly foreign-based) sport psychology consultants. Among these countries, Botswana is currently leading the way in developing locally based expertise. Throughout the Southern African region, sport, exercise, and performance psychology remain organizationally underdeveloped and unregulated. Local researchers and practitioners in the field face unique challenges, including a multicultural environment and a lack of resources. In working to overcome these challenges, however, they have the potential to significantly add value to the global knowledge base of sport, exercise, and performance psychology.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".