Bibliographic record
Abstract
This book has evolved over many years, and the number of people and institutions who should be thanked is legion.First is my wife, Gail, who has put up with the many mood swings that producing such an opus seems to entail.Then there are the undergraduate students in my various courses, who have over the years heard and read much of the book.As the book progressed it was generously supported from a variety of sources.The Social Sciences and Humanities Research Council of Canada funded an earlier conception, centred on Canada and the Vietnam War, in the late 1990s.The University of Toronto granted me a Connaught Research Fellowship in 1997, in conjunction with the same earlier version of this project.In 1997-1998, I had the privilege of a fellowship at the Woodrow Wilson Center in Washington, crucial for researching the many Canadian-American sections of the book.At a later stage the Donner Canadian Foundation came to the rescue with a grant to finish up my research in the United States.Finally, as the holder of the May Gluskin Chair in Canadian History at the University of Toronto, I have benefited from its enlightened endowment, which has allowed me to spend the past few years writing and not filling out forms begging for grants.Many friends have assisted with the conception and evolution of this work.The late Bill and Louise Armstrong, veterans of the US Foreign Service specializing in Canada, were free with advice and hospitality in Washington.Tom Delworth, former political director of the Department of External Affairs and former Canadian ambassador in Bonn, read various chapters and tried to save me from error.Allan Gotlieb, former undersecretary for external affairs and former ambassador in Washington, read the whole manuscript and was generous with his time and comments.Tom Nichols, a political scientist with a salutary hatred of jargon, helped me with the cultural context of the early 1980s -especially the relationship
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.542 | 0.287 |
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".