Bibliographic record
Abstract
In retrospect it is difficult to accept that Western democracies have implicitly supported, or at least tolerated, the legalized system of white supremacy in South Africa known as apartheid. Renate Pratt’s new book, In Good Faith , explains why the Christian churches were among the first to publicly protest, and why they provided such cogent and determined international support for the struggle against apartheid. The Taskforce on the Churches and Corporate Responsibility is a coalition of Christian churches that for nearly twenty years was one of Canada’s leading anti-apartheid advocates. As the first co-ordinator of this Taskforce, Renate Pratt was at the centre of the early anti-apartheid initiatives in Canada and consequently is able to supply a clear and accurate view. The book traces the history of exchanges between the Taskforce and successive ministers and senior civil servants of the Department of External Affairs. It details the reluctant and weak responses offered by the Canadian government and business community right up to the time of Nelson Mandela’s release from prison. In Good Faith will be of particular interest to Canadian Christians concerned with ecumenical co-operation and with the social and political dimensions of their faith. Equally, it will appeal to those interested in the impact of public interest organizations on public policy or the relationship between politics and business interests.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.068 | 0.037 |
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".