International Crisis Behavior Project, 1918-2001
Bibliographic record
Abstract
This data collection was produced as part of the International Crisis Behavior Project, a research effort aimed at investigating 20th-century interstate crises and the behavior of states under externally generated stress. To this end, the data describe, over a 83-year period, the sources, processes, and outcomes of all military-security crises involving states (with data on 956 crisis actors and 80 variables for each case). Variables were collected at both the micro/state actor level and the macro/international system level. At the macro level, seven dimensions of crisis were measured: crisis setting, crisis breakpoint-exitpoint, crisis management technique, great power/superpower activity, international organization involvement, crisis outcome, and crisis severity. Additional macro-level variables indicate various aspects of geography, polarity, system level, conflict type, power discrepancy, and involvement by powers. At the state actor level, variables measuring five dimensions of crisis were compiled: crisis trigger, state actor behavior, great power/superpower activity, international organization involvement, and crisis outcome. Additional micro-level variables indicate the role of war in each crisis. Others measure several kinds of state attributes: age, territory, regime characteristics, state capability, state values, and social, economic, and political conditions. (Source: ICPSR, retrieved 6/22/2011)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.019 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.048 |
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".