Canadian Historical Research and Pedagogy: A View from the Perspective of the Canadian Century Research Infrastructure
Bibliographic record
Abstract
In this article we explore what the exploding world of humanities and social science research infrastructures might mean for teaching and research in the discipline of history. We focus closely on one example, that of the Canadian Century Research Infrastructure Project ( ccri ). This interdisciplinary and multi-university project has constructed an infrastructure composed of microdata from the nominallevel Canadian censuses from 1911 through 1951. In addition to compiling information on approximately 2 million individuals, the ccri created a database of contextual data and a gis database. The combination of these three levels makes this infrastructure unique in the world. The ccri can be used in conjunction with Canadian census databases now being constructed or already completed for Canada from 1851 to 2001. As well, the ccri has been constructed in ways that will facilitate cross-national explorations with the United States, the United Kingdom, and several other North Atlantic countries. We suggest that the ccri can best be appreciated when situated within the current proliferation of research infrastructures across the humanities and the social sciences. We argue that these infrastructures are liberating for historians and, collectively, represent new horizons for professional activity. It would be a disservice to themselves, their students, and their profession if historians ignored these expanding horizons. Dans le présent article, nous analysons ce que pourraient être les retombées de l’éclatement de l’infrastructure dans le milieu de la recherche en sciences humaines et en sciences sociales en ce qui a trait à l’enseignement et la recherche en histoire. Nous prêtons une attention plus particulière au projet sur l’Infrastructure de recherche sur le Canada (CCRI). Ce projet interdisciplinaire et multi-institutionnel a construit une infrastructure composée de microdonnées des recensements canadiens de niveau nominal de 1911 à 1951. En plus de compiler des renseignements sur prês de deux millions de personnes, le CCRI a créé une base de données contextuelles et une base de données SIG. La combinaison de ces trois niveaux rend cette infrastructure tout à fait unique au monde. La CCRI peut être utilisée en conjonction avec les bases de données du recensement canadien en cours de construction ou déjà complétées pour le Canada de 1851 à 2001. De même, le CCRI a été construit de manière à faciliter les analyses transnationales avec les États-Unis, le Royaume-Uni, et plusieurs autres pays de l’Atlantique du Nord. Nous suggérons que le CCRI peut être le mieux apprécié lorsqu’il se situe dans la prolifération actuelle des infrastructures de recherche en sciences humaines et en sciences sociales. Nous faisons valoir que ces infrastructures sont libératrices pour les historiens et qu’elles ouvrent ensemble de nouveaux horizons pour l’activité professionnelle. Les historiens rendraient un bien mauvais service à leurs étudiants, à leur profession, et à eux-mêmes, s’ils ne tenaient pas compte de ces horizons é largis.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.020 |
| Science and technology studies | 0.043 | 0.054 |
| Scholarly communication | 0.031 | 0.011 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".