From freud to a modern understanding of behavioral, physiological, and brain development
Bibliographic record
Abstract
Seymour Levine's first "early experience" experiments were inspired by Freud. Yet, Levine's lifetime of work, and the work of his colleagues and scientists who followed, unveiled a myriad of early experience effects that even Freud himself could not have imagined. Related to and extending beyond his work on early experience, Levine also made important, often seminal, contributions to overlapping and related areas, such as early maternal separation and deprivation, maternal behavior and physiology, sexual differentiation, perinatal malnutrition, attachment in non-human primates, hypothalamic-pituitary-adrenal (HPA) stress reactivity and its adaptive significance, and the development of the HPA system. Moreover, his work spawned new lines of research by investigators active today. The papers contained in this special issue provide a sampling of research demonstrating some of the important directions in which those earliest experiments have led, many with clinical applications.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.027 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".