The History of the Brain and Mind Sciences
Bibliographic record
Abstract
How did epidemics, zoos, German exiles, methamphetamine, disgruntled technicians, modern bureaucracy, museums, and whipping cream shape the emergence of modern neuroscience? This history explores the exceptionally complex scientific and medical techniques and practices that have allowed practitioners to claim expertise in the brain and mind sciences over the past two centuries. Based on meticulous historical studies, essays in the volume move from the postrevolutionary Parisian Menagerie of the Jardin des Plantes to the political contexts of neuroscience within the National Institute of Mental Health in the United States in the late twentieth century. Touching on such disparate topics as the luggage of German exiles, the role of whipping cream in industrial food production, the emergence of neurosurgery, and the private musings of a disgruntled medicaltechnician, the contributors to this volume make a powerful case for concentrating scholarly attention on seemingly marginal chapters of the history of the mind and brain sciences. By so doing, the authors contend that it is in the obscure, peripheral, and marginal stories of the past that we can best see the emerging futures of the medicine and science of the brain and the mind. Collectively these essays thus reveal that the richness of the history of the brain and mind sciences cannot and should not be reduced to a unitary, uncomplicated narrative of progressive discovery. CONTRIBUTORS: Brian P. Casey, Stephen T. Casper, Justin Garson, Delia Gavrus, Katja Guenther, L.Stephen Jacyna, Kenton Kroker, Thomas Schlich, Max Stadler, Frank W. Stahnisch Stephen Casper is Associate Professor of History at Clarkson University. Delia Gavrus is Assistant Professor of the History of Science at the University of Winnipeg.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".