Bibliographic record
Abstract
From the end of the Napoleonic Wars to Confederation, central Canada was awash with migrants from the British Isles and their cultural values. The raw prejudice that they brought with them – against the French, the Catholics, and even Yanks and Europeans – bound together the eventual political majority in Ontario. The Orangeman uses the life of Ogle Gowan, an Irish Protestant upstart from County Wexford who turned central Canada Orange, to explore these forces. Gowan was ambitious, malicious, and mendacious, but by the time of Confederation the Orange Order was the largest alliance of men in the country – the foundation of the coalition of conservative Protestants that sculpted Canadian politics in the century that followed. Don Akenson uses his skills as a historian and a novelist in respecting the historical record. The Orangeman is a lively and entertaining fictional biography, and in Akenson’s telling Gowan crosses swords with William Lyon Mackenzie and goes pub-crawling with the young John A. Macdonald. One never knows everything about a historical person or event; sometimes the right thing to do is to speculate sensibly and, if possible, have a little fun along the way. Akenson shows us Canadian loyalism, constitutionalism, and deference to state authority on one side of the coin, and on the flip side, the successful attempt by one group of Canadians to do down the other. This is real history, real life: as yesterday, so today.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.324 | 0.188 |
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".