Commentary on an Excerpt From “Magnetism”
Bibliographic record
Abstract
This excerpt from Maupassant’s short story “Magnetism” is a wonderful testament of scientific rigor. It is uncommon to find in a classical literary work such a meticulous illustration of what contemporary epidemiologists refer to as confirmation bias or cherry-picking. Through a scrupulous method, the narrator rejects the belief that a paranormal power is behind the correlation between the death of the father and the dream of his child. To a modern physician, the text is a reminder of the evidence-based medicine paradigm and the hierarchy of evidence: Case reports (people’s beliefs in Maupassant’s story) are not about establishing evidence, contrarily to population studies (the narrator’s survey in the story). Maupassant, in his stories, actually emphasized facts. He later prefaced his novel Pierre et Jean with a statement that “psychology should be concealed in the book, as it is in reality, under the facts of existence.”1 This preoccupation with objectivity echoes the predominant standard in modern medicine: The practitioner should remain current on the existing evidence to better guide his practice. But medicine is also an art. The practitioner sometimes wields the subjective and even the irrational to better care for each patient as a whole. Biomedical knowledge by itself is not enough for the healing process: Listening to and respecting patients’ beliefs is an art form that delivers empathic support to those who need it. Once again, Maupassant’s story resonates with the physician’s experience: Delivering the bad news of a patient’s passing is a reality that practitioners commonly face. Imagine you were a guest, along with the narrator, at the dinner party Maupassant creates. Imagine as well that, weeks later, you are tasked to bring the news of a drowned sailor to a family. You come up to the door. You knock … and you tell the bad news to a spouse who suddenly becomes a widow. Past the initial shock, she tells you between two sobs that her son had dreamt of the tragic passing of his father. You then remember the explanation given during the party. How does having a rational explanation for the events affect your ability to comfort the widow? Will your attitude and choice of words betray a certain desire to set things right, to provide a rational explanation? In everyday life, as should be in medicine, the art of listening and being there for someone implies respecting, not crushing, their beliefs and explanatory models, even if those beliefs contradict scientific explanations. Just as the narrator in Maupassant’s short story dismisses magnetism as “Humbug!”, today’s physician is at risk of favoring the rational approach to that of listening and being empathic. This imbalance could lead to a dehumanization of the patient–doctor relationship. This risk is why, in the worlds of research and clinical practice, there is a strong tendency to humanize medicine—in various forms such as patient-centered care,2 narrative medicine,3 cultural competency,4 mindfulness,5 or more recently the “Montreal model” of patient partner-in-care and patient-as-trainer.6 Despite these movements, some physicians still do not practice medicine with the level of humanism that patients long for. Are the humanities overlooked in medical faculties? Perhaps the main barrier to humanistic medical care is the difficulty some physicians have balancing science and art. As people of action, physicians are constantly tempering their scientific knowledge with the particularities of the individual. As such, could they also sometimes juggle two contradicting and coexisting realities for the sole purpose of the patient’s well-being? There is certainly no perfect behavior for accompanying a family through the difficult times following the drowning of their loved one. Explaining the coincidence between the dream and the drowning might appease some families for whom a rational explanation may subdue grieving and facilitate healing or resilience; however, such an explanation may hurt others who find comfort in faith or beliefs. The narrator from Maupassant’s story says, “Just as others begin by believing, I begin by doubting.” Doubt is surely a central virtue of scientific reasoning, and scientific reasoning is a cornerstone of modern medicine. But concerning a patient’s experience, maybe the physician’s credo could be, “Just as others begin by doubting, I begin by listening.” Jean-Noel Vergnes, DDS, PhD, Nareg Apelian, DMD, and Christophe Bedos, DDS, PhD
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.023 | 0.031 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".