Bibliographic record
Abstract
In the course of his brief and brilliant life, Thomas D'Arcy McGee produced a dozen books, around three hundred poems, and countless public lectures, private letters, and newspaper articles.Many of these sources are available in microfilm or have been digitally reproduced, but many others are scattered throughout archives in Canada, the United States, Ireland, and Britain.This meant that my research on McGee was driven more by archival location than by a sequential investigation of his life.One result was that I was constantly being bounced between different phases of his career.In the same week, I might be reading his revolutionary republican pronouncements from 1848-49, his ultra-Catholic writings during the mid-1850s, and his monarchist speeches in the mid-1860s -a sometimes unhinging experience, but no less interesting for that.Another result was that my research notes were constantly in danger of spinning out of control and meandering all over the map.And so I owe a special debt of gratitude to Dana Kleniewski, who took on the task of going through all those notes and restructuring them in chronological order; as a result of her work, the challenge of refining the raw material of research into the finished product of writing was made much easier.Thanks also go to Chelsea Jeffery, who searched the debates in the Canadian legislative assembly for McGee's speeches and the reactions they elicited.As I began writing the book, numerous unanticipated questions arose, which necessitated further research.In this respect, I am particularly grateful to Leigh-Ann Coffey for the thorough, thoughtful, and reliable way in which she responded to my repeated requests for information about McGee in a wide variety of
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.365 | 0.225 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".