Bibliographic record
Abstract
This chapter is written from Duncan Ivison’s dual perspective as a political theorist and as a senior administrator at the University of Sydney, which requires him to translate vision statements about the importance of “globalizing the curriculum” into practical reality. Ivison sets out three arguments for a globalized curriculum: the civilizational rationale, the global citizenship rationale, and the rationale of taking moral disagreement seriously. Only the last provides a strong underpinning for deparochializing a curriculum by decentering Western traditions in its core design. Like the “culture wars” of the 1990s, the civilizational rationale is an argument against decentering the West very much. Its purpose is to underscore the claim that ideas of toleration and respect for cultural diversity have their origins in Western thought traditions. The global citizenship rationale, which focuses on the kinds of knowledge students need to adapt and contribute to a globalized world, may not actually generate a strong commitment to going beyond Western traditions of cosmopolitan humanism. The best alternative is based on the reality of deep and persistent moral disagreements: if only we could learn how to hear them, we might find that sometimes cultural others have persuasive arguments against views we take for granted.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".