Deliberative Political Leaders: The Role of Policy Input in Political Leadership
Bibliographic record
Abstract
This article provides a fresh perspective on political leadership by demonstrating that government ministers take a deliberative approach to decision making. Getting behind the closed doors of government through 51 elite interviews in the UK, US, Australia, Canada and New Zealand, the article demonstrates that modern political leadership is much more collaborative than we usually see from media and public critique. Politicians are commonly perceived to be power-hungry autocratic, elite figures who once they have won power seek to implement their vision. But as previous research has noted, not only is formal power circumscribed by the media, public opinion, and unpredictability of government, more collaborative approaches to leadership are needed given the rise of wicked problems and citizens increasingly demand more say in government decisions and policy making. This article shows that politicians are responding to their challenging environment by accepting they do not know everything and cannot do everything by themselves, and moving towards a leadership style that incorporates public input. It puts forward a new model of Deliberative Political Leadership, where politicians consider input from inside and outside government from a diverse range of sources, evaluate the relative quality of such input, and integrate it into their deliberations on the best way forward before making their final decision. This rare insight into politician’s perspectives provides a refreshing view of governmental leadership in practice and new model for future research.
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 | 0.032 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.033 |
| Scholarly communication | 0.021 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".