Quality of Reporting on the Vegetative State in Italian Newspapers. The Case of Eluana Englaro
Bibliographic record
Abstract
BACKGROUND: Media coverage of the vegetative state (VS) includes refutations of the VS diagnosis and describes behaviors inconsistent with VS. We used a quality score to assess the reporting in articles describing the medical characteristics of VS in Italian newspapers. METHODOLOGY/PRINCIPAL FINDINGS: Our search covered a 7-month period from July 1, 2008, to February 28, 2009, using the online searchable databases of four major Italian newspapers: Corriere della Sera, La Repubblica, La Stampa, and Avvenire. Medical reporting was judged as complete if three core VS characteristics were described: patient unawareness of self and the environment, preserved wakefulness (eyes open), and spontaneous respiration (artificial ventilator not needed). We retrieved 2,099 articles, and 967 were dedicated to VS. Of these, 853 (88.2%) were non-medical and mainly focused on describing the political, legal, and ethical aspects of VS. Of the 114 (11.8%) medical articles, 53 (5.5%) discussed other medical problems such as death by dehydration, artificial nutrition, neuroimaging, brain death, or uterine hemorrhage, and 61 (6.3%) described VS. Of these 61, only 18 (1.9%) reported all three CORE characteristics and were judged complete. We found no differences among the four investigated newspapers (Fisher's exact = 0.798), and incomplete articles were equally distributed between journalistic pieces and expert opinions (χ(2) = 1.8854, P = 0.170). Incorrect descriptions of VS were significantly more common among incomplete articles (13 of 43 vs. 1 of 18; Fisher's exact P = 0.047). CONCLUSIONS/SIGNIFICANCE: Core VS characteristics are rarely reported in Italian newspaper articles, which can alter adequate comprehension of new developments and (mis)inform political, legal, and ethical decisions.
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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 | 0.016 | 0.101 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".