NHL Attendance Differences Across the Border: United States Versus Canada
Bibliographic record
Abstract
JEL Classifications L83 • Z21This study analyzes whether there are United States (U.S.)-Canadian differences in the determinants of National Hockey League (NHL) game attendance using a panel data model.Among the Big 4 professional sports leagues in North America, the NHL is unique because seven teams are located in Canada, whereas the remaining three major leagues have at most one team located outside the U.S. (Perron & Hu, Journal of Sports Economics, 2025).Studies of NHL game attendance have investigated factors, such as the honeymoon effect of new arenas (Leadley & Zygmont, Canadian Public Policy, 2006), uncertainty of outcome (Coates & Humphreys, Journal of Sports Economics, 2012), lockouts (Treber et al., Journal of Sports Economics, 2018), winter Olympic games (Schneider et al., Economics of Governance, 2022), and locally born players (Perron & Hu, Journal of Sports Economics, 2025).However, attendance studies that differentiate between U.S. and Canadian NHL teams are less common, and they include analyses of violence (Jones et al., American Journal of Economics & Sociology,
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".