Bibliographic record
Abstract
n 1940, Marcel Cadieux, a lawyer from Montreal's working class, wrote the French-language entrance exam for Canada's Department of External Affairs (DEA).One essay topic caught his eye: "The question of Canadian unity." ✳ 1 In responding to it, he focused on French Canadians, the name used in his day for the descendants of the French settlers who came to Canada during the seventeenth and eighteenth centuries.He asserted that they needed to exercise more influence in Ottawa and should not be relegated to a subordinate economic role in Quebec.Further more, their grievances should be addressed or Quebec would not remain in Canada.When summoned before the oral examination board, Cadieux was asked only one thing by Under-Secretary of State for External Affairs O.D. Skelton: Had his essay actually dealt with national unity?Presumably, Skelton was expressing doubt about whether Cadieux had correctly interpreted the question.When Cadieux replied that it had, Skelton fell silent.Cadieux was neither hired nor told why.2 Yet he had acted on principle, something he would do throughout his career.In time, Cadieux became Canada's most
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.281 | 0.096 |
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".