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Media coverage of the persistent vegetative state and end-of-life decision-making

2008· article· en· W2108308769 on OpenAlexaff
Éric Racine, Rakesh Amaram, Matthew Seidler, Marta Karczewska, Judy Illes

Bibliographic record

VenueNeurology · 2008
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsNeuroDevNet
FundersNational Institute of Neurological Disorders and Stroke
KeywordsState (computer science)PsychologyComputer scienceAlgorithm

Abstract

fetched live from OpenAlex

BACKGROUND: Conflicting perspectives about the diagnosis and prognosis of the persistent vegetative state (PVS) as well as end-of-life (EOL) decision-making were disseminated in the Terri Schiavo case. This study examined print media coverage of these features of the case. METHODS: We retrieved print media coverage of the Schiavo case from the LexisNexis Academic database and used content analysis to examine headlines and text of articles describing Schiavo's neurologic condition, behavioral repertoire, prognosis, and withdrawal of life support. The accuracy of claims about PVS was assessed. RESULTS: Our search yielded 1,141 relevant articles published (1990-2005) in the four most prolific American newspapers for this case. The most frequent headline themes featured legal (31%), EOL (25%), and political (22%) aspects of the case. Of the articles analyzed, 21% reported that Schiavo "might improve" and 7% that she "might recover." Statements explicitly denying the PVS diagnosis were found in 6% of articles. Explanations of PVS and other chronic disorders of consciousness were rare (<or=1%). Most frequently cited descriptions of behaviors were that the patient responds (10%), reacts (9%), is incapacitated (6%), smiles (5%), and laughs (5%). Withdrawal of life support was described as murder in 9% of articles. CONCLUSIONS: Media coverage included refutations of the persistent vegetative state (PVS) diagnosis, attributed behaviors inconsistent with PVS, and used charged language to describe end of life decision-making. Strategies are needed to achieve better internal agreement within the professional community and effective communication with patient communities, families, the media, and stakeholders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.351
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations64
Published2008
Admission routes1
Has abstractyes

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