Bibliographic record
Abstract
This paper does not take the view of many scholars that parliamentary systems are presidentializing. Prime Ministers still must maintain the confidence of, at least, the lower house of parliament. In that case, divided government is not an option. Thus, it is far more accurate to talk about personalization of executive leadership. And, in that respect, presidents and prime ministers can be compared—although as with nearly every trend that has shaken the earth in the last 50 years, the US model has worked a profound effect on executive leadership elsewhere in the world.The paper will look at the US model from the standpoint of three competences plus a fourth which is a distillation of the mix a president provides. Each president must maintain responsive, strategic and fiscal competence to some degree. Responsive refers to his support. But, what is this? Is it the cluster of interests that will help him get elected, the concerns of those who will be decisive in his obtaining a second term or will it be his standing in the history books? Strategic competence used to go by the name “neutral”. But, nobody believes today that even career civil servants are entirely neutral. However, the president must ask to some degree what are the long-term consequences of his actions—in which case he is giving a nod to strategic competence. Fiscal competence concerns the balance between spending and taxing during an administration. It seems so obvious and yet, a recent administration got this terribly wrong, so we include it with the others.The distillation of these three competences is the president’s policy competence. We argue that there are incentives for a president to strive for a blend of these three. There is a natural pull in the US toward responsive competence. However it should not and, usually, does not exclude the other two. We will discuss the various mixes by presidents since Reagan. Along the way, we will assess personalization in the US and in other Anglo-American democracies. Finally, we will evaluate Barack Obama and how the new president has addressed personalization of executive leadership.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".