Profiling political leaders: cross-cultural studies of personality and behavior
Bibliographic record
Abstract
Preface Introduction by Ofer Feldman and Linda O. Valenty Assessment of Personality and Leadership: Content Analytic Techniques Studying Canadian Leaders at a Distance by Peter Suedfeld, Lucian Gideon Conway III, and David Eichhorn Political Leadership and the Democratic Peace: The Operational Code of Prime Minister Tony Blair by Mark Schafer and Stephen G. Walker The 1996 Russian Presidential Candidates: A Content Analysis of Motivational Configuration and Conceptual/Integrative Complexity by Linda O. Valenty and Eric Shiraev The Personality and Leadership Style of President Khatami: Implications for the Future of Iranian Political Reform by Tanyel Taysi and Thomas Preston Profiling the Political Personality: Psychodiagnostic and Psychobiographical Approaches Linking Leadership Style to Policy: How Prime Ministers Influence the Decision-Making Process by Juliet Kaarbo Kings, Queens, and Sultans: Empirical Studies of Political Leadership in European Hereditary Monarchies by Dean Keith Simonton Mao Zedong's Narcissistic Personality Disorder and China's Road to Disaster by Michael M. Sheng Profiling Russian Leaders from a Psychohistorical and a Psychobiographical Perspective by Juhani Ihanus Benjamin Netanyahu: A Psychological Profile Using Behavior Analysis by Shaul Kimhi The Cultural Context: Applications from East to West Building the War Economy and Rebuilding Postwar Japan: Profiling of a Pragmatic Nationalist Nobusuke Kishi by Shigeko N. Fukai When and Why Do Hard-liners Become Soft? An Examination of Israeli Prime Ministers Shamir, Rabin, Peres, and Netanyahu by Yael S. Aronoff Predicting the Performance of Leaders in Parlimentary Systems: New Zealand Prime Minsiter David Lange by John Henderson Self-Presentation of Political Leaders in Germany: The Case of Helmut Kohl by Astrid Schutz The Comparative Psychoanalytic Study of Political Leaders: John McCain and the Limits of Trait Psychology by Stanley A. Renshon References Index
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".