Canadian History Blogging: Reflections at the Intersection of Digital Storytelling, Academic Research, and Public Outreach
Bibliographic record
Abstract
This article surveys the impacts of blogging on Canadian historical practice to date. Drawing upon the experiences and practices of five collaborative or multi-author Canadian history blogs — ActiveHistory.ca, The Otter~La Loutre, Findings/Trouvailles, the Acadiensis Blog, and Borealia — it explores how this activity is changing the ways in which Canadian historians tell stories, publish their research, teach, and serve academic and wider communities. Blogging has encouraged new forms of historical storytelling and the inclusion of underrepresented and marginalized voices in public discussions of Canadian historical narratives. It is being integrated into cycles of academic publication and undergraduate and graduate classrooms. Yet challenges remain with regard to determining the place and value of blogging within standard paradigms of academic labour. As more Canadian historians come to read, write for, and edit historical blogs, however, they will not only help shift the practice of Canadian history inside and outside university campuses, but will also experience the pleasures and rewards of this kind of digital historical work for themselves.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.017 |
| Science and technology studies | 0.069 | 0.028 |
| Scholarly communication | 0.023 | 0.009 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".