CHAPTER IX The Impact of the AES on the Growth of Epidemiology
Bibliographic record
Abstract
Some 20 years ago John Gordon had occasion to refer to the growth of epidemiology in the chapter which he wrote for The History of American Epidemiology, published in 1952. Although his statement reflects the view of the Society at the quarter century mark, it still applies broadly today. Gordon wrote: two societies have contributed importantly to American epidemiology. The interests of the American Epidemiological Society are primarily those of the learned Society, concerned with the establishment of principle, the development of theory, and the evaluation of progress; and devoting attention at the annual meetings, more to work in progress than to completed studies. The Epidemiology Section of the American Public Health Association (which came into existence in 1929) serves the broader purpose of a forum for presentation of reports of work done and methods developed. It has interest in plans for epidemiological services in state and local health organizations, for the collection and utilization of data on morbidity and mortality for the study of epidemic and endemic disease, and for the selection and training of personnel for these services (1).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 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".