“Vocal but not particularly strong”? Air Canada’s ill-fated vacation package to Rhodesia and South Africa and the anti-apartheid movement in Canada
Bibliographic record
Abstract
In mid-1971, an advertisement from Air Canada (then a Canadian Crown corporation) and South African Airways appeared in the pages of the Globe and Mail, Canada’s national newspaper. It offered prospective vacationers the chance of a lifetime: the opportunity to tour the game parks of South Africa and Rhodesia, including the famous Kruger National Park, with stays afterward in various African cities. News of Air Canada’s “opportunity” was met with a great deal of controversy. Linda Freeman has described anti-apartheid forces in the 1970s as “vocal, but not particularly strong” and other scholars argue that Canadian policy toward South Africa did not change substantially between 1961 and 1984. Still, this case study demonstrates that despite the fact that no major Canadian economic, strategic, or political interest was involved in South Africa and that while Canadian trade with South Africa during the period in question was relatively marginal, the Canadian government gave the concerns of those appalled at Air Canada’s intransigence some attention. More importantly, so did Air Canada. Where government failed to act, public pressure forced a major Canadian corporation to rethink its business practices to adhere to international human rights norms.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.040 | 0.015 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".