Happy anniversary? Reflections on Samuel Huntington's “clash” thesis at thirty
Bibliographic record
Abstract
This article takes a retrospective look at the controversial “clash-of-civilizations” thesis articulated by Samuel Huntington in the early 1990s. In some respects, the “pearl anniversary” of the thesis reveals it to have stood up reasonably well. If one notable aspect of the Huntingtonian prognosis was its skepticism about the prospects of enduring peace subsequent to the ending of the Cold War, then it could be remarked that the Harvard professor turned out to be prescient. But one can be right for the wrong reasons, and the argument of this article is that Huntington erred in imagining that “civilizational rallying” would develop into the preeminent feature of future global conflict. Specifically, Huntington erred in conflating the affective pull of “nationalism” with that of “civilizationalism.”
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".