Running in circles: fenianism in rural and small town Ontario, 1865-1868
Bibliographic record
Abstract
This thesis is an investigation of the Fenian Brotherhood as it existed within rural and small town Ontario from 1865, when the Canadian government and public first became worried about the Fenians, to 1868, the year Thomas D'Arcy McGee was assassinated. Sarnia, Stratford and Guelph are examined above all other towns because they were centers of Fenian activity in the countryside and had access to the newly built Grand Trunk Railroad line. Although not as obvious or numerous as urban members, Fenians in rural locations and small towns were given an important role within the American Fenians' 1866 invasion plan and continued to operate for years after the raid was attempted. Intended to be used as support for the invading Americans divisions, rural Fenians gathered supplies and money, but more importantly, they helped recruit members and sustain the widespread rumour of a large underground Fenian army waiting within Canada. While examining how rural areas and small towns were incorporated in the original 1866 invasion plan, who the rural Fenians were and what they did as well as how the Canadian government and rural public reacted to them, it becomes clear that rural Fenians were an important faction of the organization and posed a considerable threat to Canada.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.035 | 0.013 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".