Research Article The Flexner Report of 1910 and Its Impact on Complementary and Alternative Medicine and Psychiatry in North America in the 20th Century
Bibliographic record
Abstract
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. America experienced a genuinely vast development of biomedical science in the early decades of the twentieth century, which in turn impacted the community of academic psychiatry and changed the way in which clinical and basic research approaches in psychiatry were conceptualized. This development was largely based on the restructuring of research universities in both of the USA and Canada following the influential report of Johns Hopkins-trained science administrator and politician Abraham Flexner (1866–1959). Flexner’s report written in commission for the Carnegie Foundation for the Advancement of Teaching in Washington, DC, also had a major influence on complementary and alternative medicine (CAM) in psychiatry throughout the 20th century. This paper explores the lasting impact of Flexner’s research published on modern medicine and particularly on what he interpreted as the various forms of health care and psychiatric treatment that appeared to compete with the paradigm of biomedicine. We will particularly draw attention to the serious effects of the closing of so many CAM-oriented hospitals, colleges, and medical teaching programs following to the publication of the Flexner Report in 1910. 1.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".