Grasping at the Whirlwinds of Change: Transitional Leadership in Comparative Perspective. The Case Studies of Mikhail Gorbachev and F.W. de Klerk
Bibliographic record
Abstract
This article makes a comparative analysis of transitional leadership through the case studies of Mikhail Gorbachev in the Soviet Union and F.W. de Klerk in South Africa. It examines through the prism of their political memoirs how each were able to initiate monumental change in their respective systems, but then could not hold onto power in the new political environments they helped to create. Each thought that he could construct a system that could blend old and new without negating the entire legacy of the past. Yet, each reached a point where the momentum of change pushed beyond the limits of his outlook and experience. What made Gorbachev and de Klerk able to launch change in the first place eventually made it difficult for them to function as leaders for the new age and made it difficult for people to accept them as such. Their memoirs provide poignant insight into the factors that not only enabled both of these men to become reformers, but also inhibited their capacity to become true revolutionaries.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.033 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".