Bibliographic record
Abstract
Abstract Despite the existence of a large literature on themes relating to trust and distrust in politics, there has been no sustained research on the primary objects of trust: politicians. This is an intriguing blind spot with important implications for our understanding of democratic representation and governance. This book tackles this gap head on by asking whether politicians accurately perceive and act upon the trust placed in them. In doing so, the author draws on unique survey and interview data gathered from nationally and locally elected politicians in different countries that have faced a crisis of political trust in recent decades—principally, the United Kingdom, Canada, and South Africa. The author identifies different types of ‘political trustees’ and subsequently analyses the relationship between their perceptions of trust and a variety of outcomes such as politicians’ blame avoidance behaviour and personal well-being. Taking a new and innovative approach to research on trust and elite political behaviour, the author tackles questions that are arguably of paramount importance if we are to understand when, why, and how politicians do or do not deliver on the promise of democracy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".