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Bloodletting & Miraculous Cures

2007· article· en· W154816514 sur OpenAlexaboutno aff
Jennifer Tang

Notice bibliographique

RevuePubMed Central · 2007
Typearticle
Langueen
DomaineMedicine
ThématiqueHistory of Medical Practice
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBloodlettingPortraitMedicineCourageSoulPsychoanalysisPresentation (obstetrics)SympathyPersonalityLiteraturePsychologyArt historyHistorySurgeryPsychiatryArtPhilosophyAlternative medicineTheology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Dr. Vincent Lam’s Bloodletting & Miraculous Cures is a collection of twelve short stories chronicling the lives of four physicians and the patients that they encounter. Bloodletting is an honest and revealing work, which entertains while challenging the reader to reflect on some of the ethical issues presented. The characters have strong initial presentation, but this falters towards the denouement. A scene in the anatomy lab introduces us to three of the protagonists as first-year medical students: Ming, the acerbic, scalpel-happy, left-brain dominant Type A personality, Sri, a sensitive soul who insists on naming the cadaver, and Chen, the peacekeeper who prevents Ming and Sri from vivisecting each other. Fitzgerald, the fourth protagonist, is a loner who uses alcohol to exorcise his demons. The first few stories provide the reader with portraits of these physicians in their youth, while the rest diverge into crossroads following their respective professional and personal lives. Bloodletting is an intensely personal piece that reflects the author’s experiences as a Toronto emergency physician, an Arctic research ship’s doctor, and a son of immigrants. One of the stories, A Long Migration, is based on the author’s experiences caring for his terminally ill grandfather. Dr. Lam paints poignant and often amusing sketches of the various lives touched by his protagonists; he does this most notably in Afterwards, with the embittered description of a recently widowed woman in search of the truth about her husband’s death. The most captivating aspect of Bloodletting is the author’s gift for describing his characters. In the care of his prose, Ming, Sri, Chen and Fitz are more than words on a page. As a reader, one already feels acquainted with the protagonists: they are your colleagues, friends, and classmates. The first three stories, introducing his characters as medical students, are his strongest: How to Get into Medical School Parts I and II, and Take All of Murphy. Dr. Lam breathes life into his characters by revealing their flaws, vulnerabilities and humanity. He allows the reader to become the character, suffering through the drama and anxieties they are faced with. One of the most memorable scenes is when the lovesick Fitzgerald imagines possible alternate endings to his romantic drama; the author describes this in a comical quasi-soap opera script format. The angst of applying to medical school is captured in a humorous and touching way: “They ate, clarified the puzzles of cell membrane physiology, and talked about their need to become physicians. Others were not genuine, they agreed, and transparently wanted to become doctors for money and prestige. Ming and Fitz wanted medicine for the right reasons, they told each other: service, humanity, giving. Because their motivations were clean, they were certain they deserved it more than those among them. They did not ask why they wanted to serve, be humane or to give. These simply felt like the right motivations and being correctly motivated should improve their chances of success. This was enough and these sentiments felt easy and immune from questioning.” The description of the students’ cadaver experience in Take all of Murphy is sure to stir memories of similar experiences in the minds of MJM readers. Dr. Lam skillfully intertwines various ethical questions throughout Bloodletting while still allowing his sense of humour and wit to shine through. As foreshadowed by the words of William Osler that the book begins with, the protagonists and their patients struggle with the fact that “Medicine is the science of uncertainty and the art of probability” (Osler). Although the early stories succeed in making the reader care about the characters, the latter half of Bloodletting does not live up to its full potential for character development. The second half reduces the complex features of some of the protagonists into two-dimensional forms. Ming, a fascinating multifaceted character, was given a brilliant exposition in the first story. Yet after this, she seems to be forgotten, her character left to languish without any development. She reappears briefly in An Insistent Tide, but mostly as background to another storyline. It seems a waste to see such an interesting character left behind. The gap that the reader feels in the latter half is testament to the strength of the early stories; I felt as if I had lost touch with four old friends after knowing them so well in the beginning. Regardless of this, Dr. Lam’s ability to convey moments and emotions makes this reading an enjoyable experience. Bloodletting & Miraculous Cures is a well-crafted work that offers fresh perspectives on medicine through the eyes and varied personalities of the characters. The reader is immersed in the world Dr. Lam has created through his short stories. Bloodletting & Miraculous Cures is accessible enough to appeal to non-medical audiences while still keeping seasoned health professionals engaged. It has great potential for use in medical education as a narrative that may spark interesting discussion of ethics and professionalism. In one of the stories, the author describes the thoughts of a character: “What would he be if not a doctor?” As a first novel, Bloodletting is proof that in addition to being a physician, Dr. Lam is an accomplished writer.

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)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,996
Score d'incertitude au seuil0,055

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0040,004
Communication savante0,0030,003
Science ouverte0,0010,002
Intégrité de la recherche0,0020,006
Charge utile insuffisante (le modèle a refusé de juger)0,0160,005

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 Opus0,020
Tête enseignante GPT0,271
Écart entre enseignants0,251 · 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
GenreEmpirique

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

En bref

Citations4
Publié2007
Routes d'admission1
Résumé présentoui

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