Bibliographic record
Abstract
Abstract This chapter asks whether standard theories of differences between Canada and the United States (U.S.) can explain disparities in critical social and political outcomes in the two countries. On six measures of system performance (homicides, infant mortality, poverty, economic inequality, voter turnout, and women legislators) Canada consistently delivers far better outcomes than the U.S., but examination of subnational variation reveals a more complex pattern. Most indicators differ more among U.S. states than among Canadian provinces. Within the U.S., outcomes in the northern tier of states usually resemble those in neighboring Canada more closely than they do the rest of the U.S., especially the South, which performs worst by every measure. Standard institutional and cultural theories of differences between the countries cannot explain regional variation within the U.S. nor the similarity of Northern Border states to Canada. Although obvious differences between Canadian and U.S. political institutions help account for greater homogeneity among provinces, explaining the overall pattern may require invoking such causes as climate, ethnic diversity, size of political units, and subnational political cultures.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".