Feelings of Trust, Distrust and Risky Decision-Making in Political Office. An Experimental Study With National Politicians in Three Democracies
Bibliographic record
Abstract
Tackling an important gap in the literature on political trust, this article focuses on politicians and the relevance of their other-to-self trust judgements for decision-making in public office. A unique quantitative dataset gathered from national politicians in the UK, Canada and South Africa is used to (1) examine descriptive levels of felt trust and distrust among politicians and (2) evaluate the impact of these feelings on politicians’ risky decision-making. To achieve outcome (2), this article presents the results of three survey experiments in which politicians were asked to make decisions in scenarios where both the presentation and the nature of risk varied. The results indicate that MPs’ perceptions of public trust and distrust <i>do</i> matter for risky decision-making, and that these variables moderate a reflection effect whereby MPs are otherwise more risk-averse in the face of gains and risk-taking in the face of losses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 0.000 |
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 teacher head, 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".