Crabs in the grey cup: Baltimore's Canadian football Sojourn, 1994–95
Bibliographic record
Abstract
During the early 1990s, Baltimore had a problem: replacing its professional football team, which moved to Indiana in 1984. Fans, politicians, and entrepreneurs plotted, begged, and spent millions trying to gain a replacement. But the National Football League was diffident. With scads of ardent civic suitors, the NFL played hard-to-get. By 1994, Baltimore remained on the outside, feeling desperate. At the same time, North America's “other” professional football operation, the Canadian Football League, faced troubles, too. Older than the more high-profile NFL, the CFL lagged behind its media-savvy American counterpart. Across Canada, the CFL discerned disturbing signs of ennui in its fan base. The solution came suddenly: expand the CFL into the United States, injecting elements of nationalistic competition into the staid league, and granting pigskin-hungry American cities teams to call their own. What followed was a brief, bizarre, and culturally significant episode pin North American sport history. The CFL added five American franchises, while fretting that its distinctively Canadian identity might dilute or evaporate. Most American franchises met scant fan approval. Only in Baltimore did the experiment succeed, because there singular conditions brewed a blend of civic parochialism matching Canadian nationalism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".