Review of: "State crisis theory: A systematization of institutional, socio-ecological, demographic-structural, world-systems, and revolutions research"
Bibliographic record
Abstract
Potential competing interests: No potential competing interests to declare.Very good review of the literature and a laudable attempt to establish a systematic theory of state crises.It is a very difficult enterprise because, as the author says, most of the explanatory variables are not necessarily incompatible, and so they are probably all operating to some extent.Perhaps the problem is that state crises can occur in so many different contexts; consequently some variables are operating more in some places than in others.My inclination is this is likely the case, and so perhaps it may be more manageable to try to limit the number of cases the theory is applicable to.It also would have been helpful to try to connect the conclusions to some concrete case studies of state crises; this would have allowed readers to make clearer connections between the systematic theory being defended, and the empirical phenomenon it is meant to explain
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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 | 0.011 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.030 | 0.022 |
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".