Trial Balloons and Other Adventures with Clio: John Sargent Moir, Catholic-Protestant Relations, and the Writing of Canadian Religious History
Bibliographic record
Abstract
John Moir was clearly dejected.It was the early spring, 1986, and his teaching career at the University of Toronto was winding towards a possible early retirement.He had planned a big book, perhaps one that would bring together many of the strands of research and writing that had marked nearly forty years of his dance with Clio, the muse of History.The new project was to be a history of Protestant-Roman Catholic relations in Canada.He had sought experts from both English and French Canada to support his application for a major research grant from the Social Sciences and Humanities Research Council.He had confided in me that although this would put his stamp on the question, it was yet another of what he called the trial balloons that marked his career in writing Canadian church history.Moir referred to himself, in jest, as a garden variety historian who was merely sending up a series of trial balloons on everything from Canadian Presbyterianism, church-state relations, education, and Biblical criticism, that were launched to allow colleagues and students to take aim at them with their own scholarship and try either to let them fly or pop them down.When the news arrived in this particular spring, SSHRC's negative decision shot the magnum opus balloon out of Moir's hands before he had a chance to launch it.While Moir may have taken SSHRC's
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.037 | 0.023 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 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".