Citizenship and Education in Liberal-Democratic Societies: Teaching for Cosmopolitan Values and Collective Identities
Bibliographic record
Abstract
Introduction: Liberalism and the Dilemma of Public Education in Multicultural Societies COSMOPOLITANISM, LIBERALISM, AND COMMON EDUCATION 1. Teaching Cosmopolitan Right 2. Liberal Education: The United States Example 3. Pluralism, Personal Identity, and Freedom of Conscience 4. Between State and Civil Society: European Contexts for Education 5. The Burdens and Dilemmas of Common Schooling 6. Should We Teach Patriotic History? LIBERALISM AND TRADITIONALIST EDUCATION 7. Comprehensive Educations and the Liberal Understanding of Autonomy 8. Citizenship as Identity, Citizenship as Shared Fate, and the Functions of Multiculatural Education 9. Civic Friendship and Democratic Education 10. Schooling and Cultural Maintenance for Religious Minorities in the Liberal State LIBERAL CONSTRAINTS ON TRADITIONALIST EDUCATION 11. Multicultural Accomodations in Education 12. 'Mistresses of Their Own Destiny': Group Rights, Gender, and Realistic Rights of Exit 13. Multinational Civic Education 14. Religious Education in Liberal Democratic Societies: The Question of Accountability and Autonomy 15. Liberalism and Group Identities
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".