Mental Illness, Sentencing and Execution: The Disturbing Death of an Englishman in China
Bibliographic record
Abstract
Execution is one of the indispensable means of education. Deng Xiaoping (1904–1997) Come little rabbit Come to me, Come little rabbit Let it be, Come little rabbit Come and pray, Only one people, Only one world, Only one God. Akmal Shaikh (1956–2009) The tragic saga of the execution of a British citizen, Akmal Shaikh, in Urumqi in northwest China in December 2009 highlights the risks of mental illnesses such as bipolar disorders and delusional disorders being discounted or inadequately taken into account in terms of their impact upon criminal responsibility and criminal culpability. The strong evidence is that Shaikh was seriously delusional and incapable of exercising reasoned judgements in his own best interests when he was found with heroin in his possession upon entering China. Yet he was not permitted to be examined by mental health professionals and was executed, after appeals, including to the Supreme People's Court of China, failed. The Shaikh case is a warning to all legal systems that a range of mental illnesses can generate symptoms causing those with them to have little insight but which, when properly evaluated, may be exculpatory or at least significantly mitigatory.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".