Henry Molaison’s operation for epilepsy: a case study in medical ethics
Bibliographic record
Abstract
Dr. William Beecher Scoville, an eminent American neurosurgeon of the 1940s, offered to treat Mr Molaison for his intractable epilepsy. During the operation, he removed large portions of both of Mr. Molaison's temporal lobes. Such an operation had never been performed earlier as the function of these parts of the brain was not clearly understood and neurosurgeons such as Dr. Wilder Penfield of Canada feared they could cause grave damage to the patient. Mr. Molaison developed severe loss of memory to the extent that a few minutes after meeting someone, he had no recollection of the meeting and he could not find his way to his own home. Mr. Dittrich, grandson of Dr. Scoville, has analysed the operation on Mr. Molaison's brain against the background of neurosurgery in the 1940s. This essay discusses the ethical aspects of Dr. Scoville's operation in the light of current understanding and practice.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".