Blood, it’s in you to give, just don’t be an African: the Canadian blood system and the African Indefinite Deferral Policy, 1997 to 2018
Bibliographic record
Abstract
The Canadian health care system has been the site of a tense relationship between blood donation policies and African Canadians (read as Blacks). This article explores the basis of that strain, specifically the Canadian blood system’s African Indefinite Deferral Policy and its relative underpinnings to, for example, the Creutzfeldt Jakob Disease Deferral Policy. Drawing from various data sources, the article demonstrates the subtle and diffuse aspects of the deferral policies in terms of the relationship between ethnicity and risk. The analysis provides important insights on the policies, based on the pejorative usage of ethnicity, especially its racial context, and related power dynamics, into understanding the lasting and plagued relationship that Blacks have had with the blood donation regime. Addressing questions around the institutional capacity of Canadian Blood Services and Héma Québec in dealing with minority ethnic groups is essential, particularly if the objective of blood donation policies is to address the health needs of Canada’s increasingly diverse population.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".