States of mind: The role of governance schemas in foreign-imposed regime change
Bibliographic record
Abstract
How do foreign actors involved in ‘regime change’ decide which kinds of domestic governance structures to promote in place of the regimes they have deposed? Most of the literature on foreign-imposed regime change assumes that interveners make such decisions based on rational calculations of expected utility. This article, by contrast, contends that interveners are predisposed to promote political arrangements that correspond to their own governance ‘schemas’, or taken-for-granted assumptions about the nature of political authority. These patterns are examined in relation to the US-led regime-change invasions of Afghanistan and Iraq. In both cases, the interveners appeared to be guided – and partially blinded – by their own governance schemas. Yet, if schemas have these effects, they should also be visible in cases where interveners held very different assumptions about governance and the ‘state’ than those held by US officials in Afghanistan and Iraq. To probe this possibility, this article also examines an older, non-Western case of intervention – the Mongol invasion and occupation of northern China in the thirteenth century – a case that yields similar results and highlights the need for additional historical research in this field.
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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 | 0.010 | 0.018 |
| 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 | 0.023 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".