Swearing Allegiance to No Crown: Thoughts on the Lost Histories of Municipal Rdical Politics
Bibliographic record
Abstract
T he arrival of the 150 th anniversary of Confederation presents scholars of Canada with an opportunity.This opportunity comes in the form of a temporal 'trail marker', affording us an arbitrary point, imbued with state-and culturally-created meaning, at which we may look back, look around, and look forward.From my position, at the intersections of political science, geography, and history, I choose to critically examine the past so as to optimistically consider the future.In doing so, I am brought back to an issue that has followed me through my nascent academic career: that of lost or obscured histories.It is truly difficult to critically examine the past when one is examining selective fragments.Those fragments may only exist because they aligned with previously accepted dominant cultural narratives or may simply be arranged in a way that neatly fits the aims of those who organized them as such.Possessing only historical fragments is similar to holding a book with selected paragraphs redacted.My interest in lost histories originated during my undergraduate final research project on the role of women in Hamilton, Ontario's municipal government.In subsequent conversations
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.056 | 0.075 |
| Scholarly communication | 0.021 | 0.011 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".