Bibliographic record
Abstract
Political theorists such as James MacGregor Burns (1978/2010), J. Ronald Pennock (1979), and Eric Beerbohm (2015) have argued that democratic leaders, to be democratic, must forge joint commitments with their followers before they act. But what happens when leaders act without doing so? Does this make them undemocratic? In this article, I challenge this standard, stepwise model of democratic leadership. I outline alternative models of democratic leadership that do not require leaders to forge joint commitments with their followers before they act. Democratic leaders must provide justifications for their actions, and they must be held accountable for them, but they might nevertheless act before they forge joint commitments with followers. In a trust‐based model of democratic leadership, for example, trust functions as a temporary stand‐in for justification, giving democratic leaders leeway to make decisions without first consulting their publics or forging joint commitments with them. In the hindsight model of democratic leadership, the consequences of actions can take the place of—or supplement—the justifications leaders provide. I argue that these alternative models of democratic leadership are more consistent with practices of leadership in the real world of politics. I illustrate the theory with two examples: The first focuses on Canadian Prime Minister Brian Mulroney’s decision to introduce the Goods and Services Tax in 1991; the second examines German Chancellor Angela Merkel’s leadership during the European “migrant crisis” in 2015.
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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".