Bibliographic record
Abstract
This book brings together two important streams of political science that normally do not speak to each other, the broad literature on democratization and the smaller but formidable thinking on the theory and practice of postwar peacebuilding. Since the 1990s, the editors note, the introduction of democracy in the wake of civil war has become standard practice, especially for the international community which has frequently intervened to help end brutal and protracted civil wars, such as those in Kosovo, Afghanistan, Nepal, and the Democratic Republic of Congo. The contributors to this book each assess a different facet of this practice and essentially conclude that, while the theory may be appealing, the practice is full of pitfalls. The rough-and-ready theory of the practitioners is simple enough: vote rather than fight. In the jargon of political science, interests can be articulated either through bullets or ballots, and the latter may be the solution to the former. This intuition is backed by a huge empirical literature in international relations theory which generally shows that democracies do not go to war with each other. Or so the theory goes. Whether it translates to the domestic level and to new democracies is unclear and there is a strand of theory that disputes the latter assertion. In either case, whether propounded by a UN bureaucrat or a political science professor, the practice of democratizing war-torn societies is a sobering one and often it seems that democracy and peace seem to work against each other. After all, democracy is a system of institutionalized conflict, and, it stands to reason, the last thing that war-torn societies need is more conflict. In the short run, democracy may actually work against peacebuilding and peacebuilding may require restrictions on basic liberal rights, such as freedom of the press and mass demonstrations. But in the long run, covering the simmering pot may lead it to explode and it is hard for an outsider to get it exactly right.
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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 | 0.027 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.067 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".