Notice bibliographique
Résumé
Kingston, Ontario-based portraitist Margaret Sutherland’s 2012 oil-on-linen painting Sticky asks the viewer difficult, possibly unanswerable questions. It depicts a woman, perhaps in her 60s, naked and kneeling, back to the viewer, at the foot of what we presume to be her own bed. The bed is made, but scattered with clothes—some folded, some discarded. A silly pair of pink flip-flops peeks out from under the white feather duvet which brushes the hardwood floor. There is a little daylight—one imagines an overcast day—coming from the left, which makes some, but not all of her, glow. We can’t see the woman’s face; rather, there is her gray hair trimmed at the nape of her neck, the top of her gluteal cleft, the underside of her toes aligned neatly, like a schoolgirl’s. Across her back—like scars from a whip or rows of feathers (it is difficult to decide)—is a series of sticky notes passing violent comment: Poor, Trash, Ugly, Unlovable. Who has assaulted her with these? Were they meant for her, or does she bear them for another? Did she pen them herself? Is she bent in absolution? Submission? Her face is completely hidden, so we find no hint there. We see only her aging body and the terrible judgments it bears. A standard medical narrative of this piece might run like so: “A 64 year-old woman with Class I obesity, presents in a semi-prone position. In spite of my attempt at questioning, she remained a poor historian.” I am joking, but only partly. Because isn’t this how we physicians like to sum up our encounters with people? We blame an ambiguous storyline on a patient’s inability to explain herself, rather than on our own limitations in asking liberating questions. Worse, we fail to appreciate the value of an ambiguous story. Our medical culture is built on concrete thinking, and we handle challenges to measureable outcomes poorly. For example, in their reflections on ambiguous loss (the physical loss of a loved one, but without their death, as in a disappearance or divorce, or the psychological loss of a loved one to dementia), Boss and Carnes1 argue that we physicians too quickly pathologize grief if it fails to meet our timelines of acceptable and linear mourning, à la Kübler-Ross, and we expect people to get on with things in a matter of months. They argue that we would rather call something depression than sadness. They argue that we can barely conceive that the scars of ambiguous loss may sometimes cross generations. Those of us who tolerate ambiguity less well are prone to ordering more tests and to trying more empiric treatments; we are less likely to engage in shared decision making with patients, and we are more likely to burn out.2 Either because of who we physicians were before we entered medical school, or who we became as we went through medical enculturation, we expect closure, and we crave tidy endings. Even when we attempt to be reflective in our practice, this can be true. Consider the popular Johns model of reflection.3 It urges practitioners, first, to describe an experience on the job; then, to reflect on the consequences of not only the event but also the factors that influenced decision making; and then, finally, to evaluate how the experience has changed their various ways of knowing. While this model can be useful in helping us physicians to stop to think about our work, it is also inherently libertarian and perhaps a bit Pollyannaish: challenging situation + mental homework = personal growth. I suppose this linearity is what appeals to us as goal-oriented professionals. If it worked flawlessly, however, we would all be perfect clinicians, none of our patients would … say … smoke, and neither would there be any art: There would be no questions left to ponder. We are not static, fully transparent creatures; it is human nature to constantly rework the meanings of our lives. I once heard someone say a person looks most like himself when he is just about to speak, and maybe there is a lesson in this for medicine: A patient is her truest self when she is wrestling with a question. We don’t always get answers, and we don’t always get closure. We need to learn to meet patients in their places of ambiguity, for this is where they are most vulnerable, and most truly themselves. These are the uncertainties Sticky raises for me. But perhaps more than its questions is the emotional response the painting evokes. In the back room of an empty gallery, it brought tears to my eyes. No one speaks for this woman: The sticky notes stand between me and the supplicant, gossiping. As a viewer, I am powerless to reach her. As a physician and teacher, I ask myself: Will I let the sticky notes have the final word? Monica Kidd, MSc, MD Dr. Kidd is assistant professor, Department of Family Medicine, University of Calgary, Calgary, Alberta, Canada; e-mail: [email protected]
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,015 | 0,006 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,017 | 0,025 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,027 | 0,008 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».