August 2004 Values and Interests in Attitudes toward Trade and Globalization: The Continuing Compromise of Embedded Liberalism
Bibliographic record
Abstract
We are grateful to Andrew Parkin with whom we collaborated on the original survey design, to Rod Macdonald and Klaus Stegemann for many suggestions, and to the reviewers for the Journal for constructive comments. Marnie Wallace, Patrick Kennedy, Michael Heal and Alex van Many analyses of public opinion about global integration, and by implication global governance, are based on the material factors or interests driving individual and collective political preferences. In contrast, we show that values and ideology offer a better explanation of attitudes toward trade liberalization than do economic interests, and that the material self-interest factors that do influence opinion about trade are not relevant for opinion about globalization. We use regression analysis of original Canadian public opinion data to show that individuals of whatever skill or educational level who trust multinational corporations and the market, who like the United States, who support more immigration, who oppose a larger welfare state, and who support Canada taking a more active role in the world are more likely to support globalization. We conclude that Canadians ’ continued support of free trade agreements but wariness about globalization indicates that the compromise of embedded liberalism, a compelling metaphor
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".