How do physicians respond to new medical research?
Bibliographic record
Abstract
What happens when the findings of a prominent medical study are overturned? Using a medical trial on breech births, we estimate the effect of the reversal of such a medical study on physician choices and infant health outcomes. Using the United States Birth Certificate Records from 1995 to 2010, we employ a difference-in-differences estimator for C-sections, low Apgar, and low birth weight measures. We find that the reversal of a multi-site, high profile, randomized control trial on the appropriate delivery of term breech births, the Term Breech Trial, led to a 15%-23% decline in C-sections for such births at a time when the overall trend in C-sections was rising. We find our largest estimated effects amongst traditionally disadvantaged groups (i.e., non-white, and minimal education). However, we do not find that such a change in practice had significant impacts on infant health. Contrary to prior studies, we find that physicians updated their beliefs quickly, and do indeed adjust to new medical research, particularly young physicians, prior to mandatory policy or professional guidelines.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".