Animating the Anatomical Specimen: Regional Dissection and the Incorporation of Photography in J.C.B. Grant’s <i>An Atlas of Anatomy</i>
Bibliographic record
Abstract
In 1943 Dr J.C.B. Grant, of the University of Toronto, published the first anatomical atlas ever fully produced in North America, An Atlas of Anatomy. Within the history of biomedical teaching, the publication of this textbook is remarkable for at least two reasons, both connected to the themes of animation and automation. The visual narrative of the anatomical body found in Grant’s Atlas encapsulated a paradigmatic shift in gross anatomy from a systemic approach (dividing the body into its systems) to a regional anatomy (dividing the body into areas containing interlocking systems). The contextually contingent reasons for this shift in medical training are represented in the production of this textbook. What is crucial is that anatomy is thus conceived as directly applicable to surgical practice, which intervenes on the bodies of the living, rather than the dead. The second important dimension of Grant’s Atlas was his rigorous, yet invisible, incorporation of photography into the practice of medical illustration. Grant’s Atlas systematically deployed hand-drawn tracings of photographic images in the production of his bestselling textbook to affirm an indexical connection to a ‘real body’. At the same time, this use of photography is erased within the visuals, which rely instead on hand-drawn illustrations (line-drawings and carbon-dusting) to produce this particular pedagogy of the anatomical body. The production of ‘textbook anatomy’ is thus articulated to changes in technical modes of representation (photography) and to the new techniques in print-technologies from the late 19th until the mid 20th century.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".