Let's talk about something else: how cabinet members divert issue attention in answers to parliamentary questions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Numerous studies have delved into issue attention in parliamentary questions directed at the executive cabinet, yet our understanding of cabinet members’ answers to these questions remains limited. Consequently, this paper investigates whether cabinet members strictly adhere to the issues raised in questions or actively divert attention in a different direction. Analyzing over 60,000 question-answer dyads from more than 3,000 question time sessions across the parliaments of Australia, Belgium, Canada, Croatia, and the UK, the study reveals that over 70 per cent of answers divert from or ignore issues raised in the questions. Furthermore, diversion is prominent when the prime minister answers questions, especially those from the opposition and concerning cabinet-owned matters, particularly in the early stages of the electoral cycle. This research significantly contributes to legislative studies, emphasising the importance of examining the cabinet agenda and its dynamic interaction with the agenda pursued by members of parliament.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it