Canadian studies in the new millennium
Bibliographic record
Abstract
Preface Map of Canada Introduction - Patrick James (University of Southern California) and Mark Kasoff (Bowling Green State University) 1 Canada: Too Much Geography? - Michael J. Broadway (Northern Michigan University) 2 Canadian History in North American Context - John Herd Thompson (Duke University) and Mark Paul Richard (State University of New York at Plattsburgh) 3 Politics and Government - Munroe Eagles (University at Buffalo - State University of New York) and Sharon A. Manna (North Lake College) 4 The Economy - Mark Kasoff (Bowling Green State University) and Paul Storer (Western Washington University) 5 Population and Immigration Policy - Roderic Beaujot (University of Western Ontario) and Muhammed Munib Raza (University of Western Ontario) 6 Quebec's Destiny - Louis Belanger (Universite Laval) and Charles F. Doran (Johns Hopkins University) 7 Literary and Popular Culture - Andrew Holman (Bridgewater State University) and Robert Thacker (St. Lawrence University) 8 Native Peoples - Michael Lusztig (Southern Methodist University) 9 Women's Issues - Patrice LeClerc (St. Lawrence University) 10 Environmental Policy - Leslie R. Alm (Boise State University) and Ross E. Burkhart (Boise State University) 11 Civil Society and the Vibrancy of Canadian Citizens - Lea Caragata (Wilfrid Laurier University) and Sammy Basu (Willamette University) 12 Canadian Foreign Policy - Douglas Nord (Western Washington University) and Heather Smith (University of Northern British Columbia) 13 Trends and Prospects - Mark Kasoff (Bowling Green State University ) and Patrick James (University of Southern California)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.005 |
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".