Ordering suicide: media reporting of family assisted suicide in Britain
Bibliographic record
Abstract
OBJECTIVE: To explore the relationship between the presentation of suffering and support for euthanasia in the British news media. METHOD: Data was retrieved by searching the British newspaper database LexisNexis from 1996 to 2000. Twenty-nine articles covering three cases of family assisted suicide (FAS) were found. Presentations of suffering were analysed employing Heidegger's distinction between technological ordering and poetic revealing. FINDINGS: With few exceptions, the press constructed the complex terrain of FAS as an orderly or orderable performance. This was enabled by containing the contradictions of FAS through a number of journalistic strategies: treating degenerative dying as an aberrant condition, smoothing over botched attempts, locating the object of ethical evaluation in persons, not contexts, abbreviating the decision making process, constructing community consensus and marginalising opposing views. CONCLUSION: The findings of this study support the view that news reporting of FAS is not neutral or inconsequential. In particular, those reports presenting FAS as an orderly, rational performance were biased in favor of technical solutions by way of the legalisation of euthanasia and/or the involvement of medical professionals. In contrast, while news reports sensitive to contradiction did not necessarily oppose euthanasia, they were less inclined to overtly support technical solutions, recognising the importance of a trial to address the complexity of FAS.
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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 | 0.003 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".