Bibliographic record
Abstract
This article recounts the author’s career as a public historian, involvement in academic writing, and aspects of his philosophy of history as they pertain to changes and continuities in historical practice and current trends in the field of Canadian history. It follows his path from undergraduate studies at Brandon University, graduate work at the University of Manitoba, and his thirty-five-year career at Parks Canada while based in Winnipeg, Ottawa-Gatineau, Victoria, and Vancouver. Also elaborated are his various activities in heritage conservation and public history, service on boards and committees, and his principal publications, how they came about, and the content of these works. The article credits some of the intellectual influences and historical mentors who helped shape his development as a historian. His early grassroots political activism and community engagement are also touched upon insofar as they influenced his approach to history. Also recounted are some of the challenges he was obliged to overcome in order to become a successful public servant, scholar, and consultant involved in the wider community of history and heritage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.041 | 0.070 |
| Scholarly communication | 0.027 | 0.013 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".