Bibliographic record
Abstract
This article explores the erratic history of counting by race on the Canadian census. It argues that the political development of racial classifications on Canadian censuses has been shaped by the interactions among evolving global ideas about race, the programmatic beliefs of international epistemic communities of statisticians and census designers, and domestic institutions involved in the administration of the census. First, Canadian census designers drew from shifting global conceptions about the nature of race and racial difference, which normatively defined the legitimate ends of race policies. Second, Canadian census designers often paid heed to the programmatic beliefs of the international statistical community about the appropriateness of collecting racial data. Finally, evolving political institutions involved in the administration of the census mediated these transnational ideas, molding them to fit the Canadian national context through institutional and cultural translative processes. Theoretically, this research makes the case that focusing on interactive political development can augment the theoretical toolbox of American political development, enabling a more comprehensive picture of the emergence, dynamism, and persistence of the Canadian racial order.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.024 | 0.038 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".