Bibliographic record
Abstract
The article is wrinkled and aging.The photograph of U.S. Ambassador David Wilkins in an Ottawa Senators jersey smudged and faded.I cut out the story in December 2005 when I was home in Winnipeg for the Christmas holidays.I had moved to Los Angeles a few months earlier so the picture of Wilkins in the Winnipeg Free Press with the headline "We're slow and 'stalk-k k ing' America, says TV pundit" caught my attention.MSNBC's Tucker Carlson had just made his infamous "Canada is your retarded cousin" comment and the Canadian press was indignant at this latest verbal slight as well as some other equally provocative Canada-bashing remarks.As a journalist and now an incognito Canadian, I was intrigued.Why were American commentators taking aim at Canada?And how did this compare to what has been said by the American media in the past?So began the process of sifting through thousands of newspaper and magazine articles, trolling the Internet for anti-Canadian blog postings and keeping track of television comments.In essence, it is a project with no finite end.I want to thank all those who contributed in even the smallest way to this book.To my family and friends who offered encouragement and passed along tidbits they heard or read in the news; to those who always picked up the phone when I called and helped me navigate writer's block; to my husband Ryan who rallied behind
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".