From Birth in a British Orphanage to Assessments of American Indians’ Development
Bibliographic record
Abstract
Jane Costello, Professor Emerita of Psychiatry and Behavioral Sciences at Duke University (United States) was born in England (1939) and received her PhD in social psychology from the University of London School of Economics. She participated in two National Academy of Medicine (United States) panels on aggressive and violent behavior. She began her career as an epidemiologist and evolved into a developmental epidemiologist, incorporating methods from the developmental sciences. Her interest in aggressive behavior started with studies of children with psychiatric illnesses. She created the DSM diagnostic interview for children. She studied the role of puberty in the development of conduct disorder. She created the Great Smoky Mountains Study in the United States, which led to an opportunity to compare the development of American Indian and non-Indian participants in response to a ‘natural experiment’: the creation of a casino. It had no effect on the children of the well-off members of the American Indian community, but it had a marked positive effect on children from poor families, even into their 30s. Results point to a critical period of exposure early in the teenage years: a bio-psycho-social phenomenon, which also has considerable economic and social effects, similar to the expected effect of a ‘Universal Basic Income’ (UBI).
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".