Brexit, Cabinet Norms and the Ministerial Code: Are we Living in a post‐Nolan Era?
Bibliographic record
Abstract
Abstract The Nolan Report will celebrate its twenty‐fifth anniversary in 2020, and for most of this last quarter‐century, it has provided the underlying ethical basis for public life in the United Kingdom. However, its principles are now being called into question in a number of areas, following the Conservative government’s loss of its parliamentary majority in the 2017 election, with the interests of party taking precedence over adherence to both the spirit and the codified practical implementation of some of the ultimate outcomes of Nolan, namely the Ministerial Code and the Commissioner for Parliamentary Standards. This article argues, with explicit evidence and examples, that ministerial conduct which would not have been tolerated before 2017 is now being routinely ignored in the interest of maintaining party unity in order to deliver some form of Brexit. The article concludes by asking whether Nolan norms still command consensus post‐Brexit.
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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 | 0.026 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.047 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".