Bibliographic record
Abstract
tables Writing this book has been very much a labour of love.Stanford Reid was not only my honours adviser at McGill, he was interim moderator when I served the Mille Isles Presbyterian Church from 1957 to 1959 and, over the years, a frequent visitor and trusted friend with whom I shared many projects and interests.Thus, I cannot claim total objectivity in the composition of this book.At the same time I cannot take credit for his opinions, some of which are highly controversial.He was outspoken and opinionated, and his papers demonstrate that quality of strongly held views.Many people have travelled with me in this seven-year odyssey of discovery.Stanford Reid's papers are scattered in the archival collections of at least four institutions: Westminster Seminary; the University of Guelph; the Institute for Christian Studies in downtown Toronto; and particularly the Presbyterian Church in Canada (pcc), to whose archives he consigned the bulk of his material, including four indispensable scrapbooks.It would be impossible for me adequately to thank pcc archivists Kim Arnold and Bob Anger for their cheerful assistance.Stanford Reid's papers there are in the process of being meticulously catalogued, a boon I did not have in the early stages of research on this book.I would like to thank the four trustees of the Priscilla and Stanford Reid Trust, who have provided unfailing encouragement and support.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.441 | 0.237 |
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".