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Record W2613337038

See No Evil: The Bedside Spectatorship of Vivian Bearing

2017· article· en· W2613337038 on OpenAlexaff
Elizabeth E. McElroy

Bibliographic record

VenueVerso: An Undergraduate Journal of Literary Criticism · 2017
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAmbivalencePsychoanalysisPower (physics)ConsciousnessPaceAestheticsDutySociologyPsychologyLawArtPhilosophyEpistemologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

In this thoughtful essay, its author Elizabeth McElroy explores Margaret Edson’s celebrated play “Wit” with a focus on biomedical ethics, namely, the attitudes toward the dying that the play’s hospital setting might encourage or, indeed, discourage. McElroy’s opening gambit is to set Edson’s play alongside Freud’s claims regarding the potential for theatre to expose its spectators to the experience of death. Pace Freud, we are all hardwired to avoid any sense of our own death for the deceptively simple reason that consciousness literally cannot grasp it; try as we might to imagine our own deaths, we are always there as spectators in that very act of imagining. Despite Freud’s own ambivalence to the powers of actual theatrical spectatorship—a spectatorship that both brings death closer and holds us at a safe distance from it— McElroy resolves to deepen and complicate Freud’s idea of spectatorship by exploring the various modes of looking that are played out in “Wit”: the observational power of the attending physician-researchers, for whom the protagonist Vivian Bearing is ‘research’; the compassionate regard of the duty nurse; and finally, the play’s breaking of the fourth wall, which allows for a more fundamental experience of looking at the dying, one that is rendered all the more complex because it is accompanied by the experience of being looked at by the dying. In a skillful treatment, McElroy ties the play’s different modes of looking to recent bioethical considerations of best practice in terms of patientphysician relationships. —Sarah Clift

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.331
Teacher spread0.299 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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