Bibliographic record
Abstract
It is customary in books such as this to include "Suggested Readings" or something similar, intended to direct students to key sources.Students of Canadian foreign policy are fortunate to be able to draw on a rich array of primary and secondary sources, in English and in French.However, the burgeoning literature in the field makes identifying key sources an increasingly daunting task.In this book, we take a somewhat different approach.While we do provide a brief discussion below with some illustrative sources for further reading and research, our "suggested readings" are to be found in each chapter's notes.Notes serve two purposes.First, they are the traditional means of providing readers with the source of quotations, research, interpretation, or ideas.Second, notes act as a kind of hypertext, providing additional information about a topic in the text.We use notes for both these purposes, and we are hoping that our readers will not only explore the endnotes for additional information, but will also use the notes in this book as a bibliographical guide.We have tried to ensure that the references are as full as possible, not to be pedantic, but to point the way to those scholars who have treated subjects in greater depth than is possible in a survey such as this one.We also provide a number of sources in French, a reflection of the vibrant scholarship on Canadian foreign policy that often remains largely invisible to many students at English-speaking universities.We hope that just as students at French-language universities routinely read the work of English-speaking scholars, readers of this book will read the contributions of francophone scholars.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.092 | 0.041 |
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".