Programmes of frivolity on ice? Hockey, business, diasporic identity and apartheid in South Africa, 1936-1992
Bibliographic record
Abstract
South Africa has a surprisingly long history of the sport perhaps most usually associated with the northern hemisphere: ice hockey. Ice skating was first introduced in the country in the last decade of the nineteenth century as a commercial venture. Entrepreneurs built ice rinks for profit-making purposes and brought showmen from overseas to demonstrate the sport. An ancillary activity was the establishment of ice hockey clubs in 1936 and beyond. Given the strong profit motive, personal and tactical differences between the chief investors and sports administrators inevitably left its imprint on the sport. The extensive involvement of German, Canadian and Swiss immigrants throughout the twentieth century also co-determined the eventual character of the sport. From its inception through to 1991, ice hockey practised racial segregation, operated within apartheid laws and remained an exclusively white activity. Unsurprisingly, the apartheid ice rink also became embroiled in global politics, became a target of the worldwide anti-apartheid sports boycott and was excluded from all international competition from the late 1960s until 1991. This article reclaims some of ice hockey's neglected history in South Africa and investigates the interplay of sport, ice rink entrepreneurship, imperial and foreign identity, and apartheid politics during the twentieth century.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".