Bibliographic record
Abstract
Benjamin B. Lahey was born in 1945 in the United States. He is the Irving B. Harris Professor of Psychiatry at the University of Chicago and was President of the International Society for Research in Child and Adolescent Psychopathology. He received the U.S. National Academy of Neuropsychology research prize for his work on attention-deficit/hyperactivity disorder. He first conducted research on the effectiveness of behavior therapy with school children. He then created a reliable and valid assessment of psychological problems for large samples of children. He directed the American Psychiatric Association field trials on disruptive behavior disorders in children. With Rolf Loeber, he also created a longitudinal study of clinic-referred prepubertal boys with problems of hyperactivity and serious conduct problems: The Developmental Trends Study. He also created a large cohort of twins to study the genetic and environmental contributions to conduct disorder. Results led him and his colleagues to propose a hierarchical causal model of psychological problems in which he hypothesized a general factor of psychopathology that plays a central role. The key idea is that the causes and mechanisms of each dimension of psychological problems cannot be studied and understood separately; they are far too intertwined.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.169 | 0.096 |
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".