Developing a Measure of Generative Historical Consciousness From Political Leaders’ Speeches
Bibliographic record
Abstract
The desire for power causes wars, oppression, and destruction, yet power is a necessary dimension of all human enterprises. Therefore, taming power is a central moral and political problem in the social sciences and humanities, as well as politics and religion. This article reports development of a content analysis measure that differentiates expressions of “tamed” and “untamed” power, based on the theoretical concept of generative historical consciousness (GHC). We describe the GHC concept and measure and report results from four studies establishing their validity in differentiating expressions of tamed versus untamed power. The first study uses matched pairs of world leaders’ texts on various political themes—for example, crisis escalation versus détente, vengeance versus reconstruction, and treatment of minority groups. Two case studies compare texts from different career- and life-stages of Malcolm X and Nelson Mandela. A final study compares two speeches about the Middle East by U.S. President Barack Obama.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 teacher head, 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".