The president and the vice president: Different types of partnerships for a unique power couple
Bibliographic record
Abstract
Abstract As the vice presidency evolves over time, the way we assess vice presidents' activities and influence also needs to change. We must consider the type of partnership that the president and the vice president develop together, which determines not only the latter's involvement in the decision‐making process but also the scope of his or her influence. Since partnerships can change from one term to another and according to the issues, they can help explain the fluctuations of vice presidents' influence within and between administrations, but they also enhance our comprehension of the evolution of executive power by emphasizing the dynamics of the connection between its principal components—the presidency and the vice presidency. This article introduces a new typology accounting for four different partnerships: communication, coordination, cooperation, and collaboration. This typology distinguishes between weak and strong partnerships, depending on the level of influence they allow the vice presidents to exert. Partnerships are defined by a series of criteria related to the selection of the running mate, the tasks of the vice president within the administration, and the quality of his or her relationship with the president.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".