2013 Canadian Historical Association Presidential Address: On Local History and Local Historical Knowledge
Bibliographic record
Abstract
This article considers two undervalued aspects of historical production — local history and local historical knowledge. It distinguishes between microhistory as carried out by professionals and local history as practised by vernacular historians, sometimes in collaboration with professionals. Relating his own experience with the genre of local history, the author highlights the importance of local historical knowledge as held and transmitted by community elders. His collaboration with the Elders of the Inuit community of Grise Fiord, Nunavut, is discussed as an illustration of its potential. The collaborative and dialogical character of local historical knowledge is further exemplified by folklorist Henry Glassie’s work with a small Northern Irish community. Noting current challenges of changing demographics, uprootedness and diaspora, the article considers how emerging communities and minorities are recreating new opportunities for local historical knowledge in Canada’s cities. Heeding the advice of senior Elders such as the late William Commanda of the Algonquin First Nation at Maniwaki, Quebec, the author asserts the importance of local historical knowledge to Canadians’ identities as members of communities with a common history, strengthening connections between people, past and present, and positioning us to better face the future.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.022 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.078 | 0.007 |
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".