Bibliographic record
Abstract
Abstract The Macy Conferences on Cybernetics were a series of 10 interdisciplinary scientific meetings that took place in New York between 1946 and 1953. The meetings were sponsored by the Macy Foundation, which aimed to promote interdisciplinary approaches to the social, behavioral, and medical sciences. Co-organized by neuropsychiatrist Warren S. McCulloch and Frank Fremont-Smith, medical director of the Macy Foundation, the meetings brought together a variety of scientists from mathematics, psychology, engineering, anthropology, physics, ecology, psychiatry, neurophysiology, linguistics, and sociology. The conferences strove to apply tools from the physical sciences and mathematics to problems in the biological and human sciences. Such tools stemmed first from Norbert Wiener’s work on the anti-aircraft predictor, in which he employed the concept of negative feedback to explain purposeful behavior, and second from McCulloch’s work with Walter Pitts on the logic of neural activity, which purported to embody logical reasoning in the physiology of the brain. Wiener and McCulloch touted the practice of hypothetical modelling as a bridge over the divide between the natural and the artificial, and a method for explaining purposeful behavior in organisms and machines. Discussions at the Macy Conferences expanded on this work, and participants discussed and debated models of cognitive functions such as sensation, communication, memory, and learning, all cast as functions of the mind and exemplars of purposeful behavior. Thus, the meetings signal a major shift in 20th-century psychology, when discussions of the mind took on a more central place in psychological discourse. Behaviorist psychologists in the early 20th century had largely rejected concepts of mind as unscientific and not objective. The Macy Conferences, in contrast, placed the mind at the nexus of interdisciplinary inquiry across the divide between the physical and human sciences, and helped to bring back the mind as a topic of objective, scientific inquiry in psychology and in the emerging cognitive sciences.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.019 | 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".