The Canadian National Bibliography: 50 years of continuity and change
Bibliographic record
Abstract
It is a pleasure for me to be here today to share with you the celebration of the 50 th anniversary of Canadiana, Canada’s national bibliography. I speak on behalf of all of my colleagues at the National Library of Canada in saying we are proud of our bibliographic heritage and it is an honour for me to be the person having this opportunity to tell you about the creation and evolution of our national bibliography and some of our hopes for its future. The theme of our session today asks a question: Is bibliography indispensable or redundant? Certainly, in the early days of Canada’s history, there was no question as to the need for bibliographic services. Our first prime minister, Sir John A. Macdonald, identified the need for a national library not long after the country was created in 1867. Throughout the decades of the first half of the 20 th century, librarians and researchers repeatedly lobbied the Government of Canada to provide two essential services: bibliographic control of Canadian publications and identification and location of these resources for loan. Given the other more pressing priorities in the years immediately following the second world war, it is a tribute to the government of the day that it approved the creation in 1950 of the Canadian Bibliographic Centre to compile and publish a national bibliography and to create and maintain a national union catalogue.
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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 | 0.036 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.030 |
| Science and technology studies | 0.046 | 0.054 |
| Scholarly communication | 0.048 | 0.024 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".