Conceptualizing and Constructing the Canadian Century Research Infrastructure
Bibliographic record
Abstract
The Canadian Century Research Infrastructure (CCRI) is an interdisciplinary, multi-institutional, and internationally linked initiative to enable research on the making of modern Canada. At the heart of the CCRI are microdatabases centered on the manuscript census enumerations for 1911, 1921, 1931, 1941, and 1951. This research infrastructure will be added to the results of other projects that cover the periods from 1852 to 1901 and to the Statistics Canada (STC) census microdatabases from 1971 to 2001. When completed in 2008, the CCRI will thus enable research to be made on the individuals, families, households, and communities that experienced the complex transformations of Canada since the mid-nineteenth century. By analyzing approaches to the epistemological issues involved in building the CCRI, the author seeks to advance scholarly debate by describing the research infrastructure's distinguishing characteristics and explaining its various components that seek to both support and facilitate research projects. This overview provides the context for the three other articles in this theme issue of Historical Methods that focus on CCRI's sampling and census microdata management strategies as well as the initiative's georeferencing and contextual data systems.
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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 | 0.033 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.026 |
| Science and technology studies | 0.029 | 0.079 |
| Scholarly communication | 0.039 | 0.017 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".