Professor John Waterlow CMG FRCP FRS in interview with Dr Max Blythe: Part 1
Bibliographic record
Abstract
Part one At the start of the interview Professor John Waterlow, professor of nutrition at the London School of Hygiene and Tropical Medicine, speaks of his ancestors - including the Lord Mayor of London Sir Sydney Waterlow - and his childhood and education at Summer Fields in Oxford and Eton College. A talk by Tubby Clayton of Toc H on leprosy in West Africa led to a decision to study medicine. Professor Waterlow then talks about his pre-clinical years at Trinity College, Cambridge. He reflects on his interest in left-wing politics as a student, his medical studies - here he acknowledges the influence of the physiologist Sir Joseph Barcroft, his supervisor the neurophysiologist Alan Hodgkin, the biochemist Sir Frederick Hopkins, and HA Harris, professor of anatomy - and his marriage to Angela Gray in 1939. Next, he describes his clinical studies at The London Hospital 1939-1942; his time at the North Middlesex Hospital, Edmonton where he worked for the superintendent and pioneering surgeon Ivor Lewis, learning about midwifery at Mile End Hospital, Stepney, and casualty work at Aldersbrook Hospital in Walthamstow. He comments on the difficult conditions due to bombing, the lack of formal teaching in some areas and the high levels of responsibility thrust on students due to depleted staff. The interview moves on to Professor Waterlow's decision to concentrate on physiology and his first appointment at the MRC Military Personnel Research Committee at the National Hospital, working with EA Carmichael and Ben Platt. He talks of Platt's career to that date, the development of interest in nutrition in the 1930s, his first posting to investigate heatstroke and heat exhaustion in the Persia-Iraq forces, investigations into protection against the effects of heat and poison gas at Queen Square, and the birth of his three children. Professor Waterlow then outlines his next career move, which would inform the direction of the rest of his working life. Persuaded by Ben Platt to investigate nutrition, he was posted to Trinidad, Guiana and Jamaica, where he investigated the high mortality rate among children. This was to be the start of many years interest in liver metabolism. He describes his work, pioneering in its emphasis on measuring the fat in the livers of afflicted children, and his realisation on returning to England that this was the kwashiorkor described by Cicely Williams. At the end of interview Professor Waterlow discusses his return to England and his early work with the Cartesian diver, building on the work of Linderstrøm-Lang.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".