Back to the Future: Historical Political Science and the Promise of Canadian Political Development
Bibliographic record
Abstract
Abstract How “historical” is Canadian political science? This paper sets out to answer this question through an analysis of historically oriented articles that have appeared in this journal from its first volume, in 1968, to 2015. We suggest that historical research in this journal is at once enduring and uneven, a pattern that we then explore in more detail in a case study, spanning forty years, of historical articles that focus on the interconnected themes of the constitution, courts, and federalism. The unevenness of this pattern suggests that the intellectual and methodological foundation of “historical” Canadian political science may not be as firm as it appears. We therefore conclude with a description of some methodological and conceptual tools, originally fashioned within the historically oriented subfield of American political development in the United States, that Canadian political scientists might deploy to probe important and enduring questions of Canadian politics.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.027 | 0.037 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".