The Cognitive Processing of Politics and Politicians: Archival Studies of Conceptual and Integrative Complexity
Bibliographic record
Abstract
This article reviews over 30 years of research on the role of integrative complexity (IC) in politics. IC is a measure of the cognitive structure underlying information processing and decision making in a specific situation and time of interest to the researcher or policymaker. As such, it is a state counterpart of conceptual complexity, the trait (transsituationally and transtemporally stable) component of cognitive structure. In the beginning (the first article using the measure was published in 1976), most of the studies were by the author or his students (or both), notably Philip Tetlock; more recently, IC has attracted the attention of a growing number of political and social psychologists. The article traces the theoretical development of IC; describes how the variable is scored in archival or contemporary materials (speeches, interviews, memoirs, etc.); discusses possible influences on IC, such as stress, ideology, and official role; and presents findings on how measures of IC can be used to forecast political decisions (e.g., deciding between war and peace). Research on the role of IC in individual success and failure in military and political leaders is also described.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".