Bibliographic record
Abstract
Abstract The main focus of Chapter 4, in terms of the powers of the courts to address electoral wrongdoing, is section 115 of the Representation of the People Act 1983, which prohibits the use of a ‘fraudulent device or contrivance’ to induce an elector to give or refrain from giving his or her vote. A key question is, how widely was the prohibition intended to extend? Consistent with the theme developed throughout the book, the answer to that question will be that the prohibition was concerned with electoral participation fraud, and not with political viewpoint fraud. Having shown how the historical context demonstrates that this was so, the chapter examines the merits and demerits of expanding the scope of section 115-type offences to cover political viewpoint fraud or disinformation. It is argued that such an expansion is wrong in principle. In that regard, the focus is not so much on the substantive political case for tolerating the dissemination of political viewpoint fraud, but on an argument that such an expansion wrongly places the judiciary in a position in which they have to take an overtly political approach to adjudication, in determining the applicability of criminal sanctions. To that end, there is consideration of case law development in England, and in Canada and Australia, analysing the different approaches that have been taken.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".