Bibliographic record
Abstract
South of the Borderpa u l k r u g m a nIn his conclusion to this chapter, Paul Krugman notes that "if the US moves away from a strong welfare state, it will diverge sharply from other advanced countriesincluding Canada."Conversely, in attempting to integrate further with the United States, could Canada move away from being a welfare state?The intriguing conjecture in Krugman's paper is that if income distribution remains more equal in Canada than in the United States, and thus continues to more closely resemble that of the Northern European countries, Canadian voters acting rationally will show a preference for state provision of essential services, unlike voters in the United States, who, if acting rationally, might on average be averse to such provision.It's easy to see why residents of the US tend to forget that Canada exists.The linguistic boundary in North America runs through the middle of Canada, not between the nations.The threat of terrorism has led to strengthened border controls, yet the frontier remains remarkably open.And the cultural interaction between the nations is, of course, enormous in both directions.Given all this, one might expect to find strong similarities both in political attitudes and in economic and social policy.Yet when it comes to taxes and public services, the border is wide, indeed.Canada collects about 10 per cent more of its gross domestic product (gdp) in taxes than the United States.It provides universal health care; it offers substantially more generous assistance to low-income families.Largely thanks to much higher spending on income security, Canada has substantially lower poverty rates than the US, especially among children.And even these measurable differences fail to capture the full difference in attitudes.Canada's welfare state is no longer as generous as it was a
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.085 | 0.012 |
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".