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Room for a view : Flesh

2001· article· en· W2407509250 sur OpenAlexvenueno aff
Lara Hazelton

Notice bibliographique

RevueCanadian Medical Association Journal · 2001
Typearticle
Langueen
DomaineMedicine
ThématiqueEmpathy and Medical Education
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFleshComputer scienceWorld Wide WebData scienceInformation retrievalBiologyFood science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

These charts are the biographies of the patients in the dark rooms. They tell part of the story — that which can be compared against normal values. Yet they have been abridged, just as the subjects themselves have been sorted into systems, prodded and scanned, disembowelled, their internal organs pulled out. The person has been condensed into a problem list, lines on a graph, lab values, brief words on a nursing flow sheet. The dimensions of life have been filed into a binder with a wheel that flags orders as routine or urgent. In this way we dismantle the living person with surgical precision. Dr. K, the palliative care specialist, wants to include patients' photographs in the charts in the hope that this will stop the process of disintegration. To illustrate this, he produces a medical photograph of the usual sort: a subject posed like a mannequin, eyes cut off at the edge of the frame to preserve confidentiality. The mouth is pulled into a grimace by fibrosing tissues, and the overexposed skin of the man's chest shows the cutaneous manifestation of the cancer moving through his veins. Then, in contrast, he shows me a moody, contemplative black-and-white image of the same man lying in bed, looking away. See the textured sag of the skin on the bone, the way the soul binds the tissues together into a face? I watch Dr. K as he considers the photograph, taking in the shadows around the man's eyes. He knows the ending to the story, whether the man has lived or not, yet he looks at the picture as if waiting for an answer. The artist's gaze, the physician's gaze. The subject: the living and the dead. One night as we watch television, my husband tells me about a Web site his students have shown him. Posted on it are photographs of dead bodies: autopsies, suicides, murder victims. During the commercial, we argue idly about whether or not that sort of thing should be on the Internet. I'm not entirely opposed. Maybe people would be less prone to romantic fantasies about shooting themselves in the head, et cetera, if they had a visual to go with it. My husband disagrees. He doesn't think those images should be there to be stumbled upon by the unwary. “They were terrible pictures,” he says. “I just keep seeing them in my mind.” I tell him I'm surprised at his reaction. He was there those nights in my first years of medical school when I came home with bits of brain and flesh clinging to my clothes. He knew what I was doing up there on the thirteenth floor of the medical school building, slowly taking people apart week by week, creating pictures like the ones he finds so shocking. Yet I always knew that he wouldn't want to see what I saw. I wouldn't have felt right about showing him. That year in the dissecting lab, surrounded by bodies like investigators of a mass murder, there was a line being drawn, a border between those of us who had seen and those we had to protect. The secret we kept — what others would never really understand — was how little it bothered us. For us medical students, it was just part of our training to take people apart like that. It doesn't hurt them, we would think to ourselves as we made tentative cuts with the scalpel. This isn't alarming: look, no one else is alarmed. These pictures can fade from your mind. These people can disappear bit by bit until nothing remains. There are already some charts in the hospital that have photographs in them. In the dementia units, where there is the risk that a patient will elope, escape, some representation is needed to identify the missing. What gets caught by the Polaroid is the face of a convict, a criminal mug shot taken against the unit door. Some of the elderly models manage a smile: those who can still be coaxed into it, or who perhaps remember what to do when a camera flashes. Others have no recollection; their faces are flat, washed out beneath red and glowing eyes. Such photographs record the last stage of a journey begun a lifetime ago with baby pictures on a studio photographer's couch. They are sufficient for identification purposes. If it were not for the fact that so many of the subjects are already half-departed, who knows whether or not it might make them more human? There are maybe a thousand charts or more that have my writing in them, buried away in cabinets in warehouses, shrunken into tiny blocks of microfilm. They contain my impressions of patients, descriptions of what went on while they were in hospital. My own form of immortality as well as theirs. I think about what could be read between these lines, how the negative contours of myself have been left behind like fingerprints on the record. Each one is a story of me, a picture of me. But my shape was lost, too. With every word I wrote, I dissolved — into the assessor, the helper, the one too afraid of making a mistake. Once or twice, while flipping through a patient's old records, I have encountered my own handwriting or dictation from years before, with my signature on it. It is an odd sensation, as if I were encountering my own ghost in the chart. I read these notes, staring into my eyes, trying to recognize myself. Notice how distant I sound, how detached. How did I feel when I wrote that: pleased, angry, discouraged, or anxious just to get it down and go home? What if there were a photograph included in the chart, one that had caught my expression at the moment before I made up my mind about the case? That caught the uncertainty before it was forbidden, recorded the emotion I tried to exclude from what I wrote? I can almost imagine how seeing this could form flesh again around my bones, and how I might be pulled back, struggling, into my own skin.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,817
Score d'incertitude au seuil0,261

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,005
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0030,001
Communication savante0,0060,005
Science ouverte0,0010,005
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,8170,549

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,295
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2001
Routes d'admission1
Résumé présentoui

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