Undercontrolled Temperament at Age 3 Predicts Disordered Gambling at Age 32
Bibliographic record
Abstract
Using data from the large, 30-year prospective Dunedin cohort study, we examined whether preexisting individual differences in childhood temperament predicted adulthood disordered gambling (a diagnosis covering the full continuum of gambling-related problems). A 90-min observational assessment at age 3 was used to categorize children into five temperament groups, including one primarily characterized by behavioral and emotional undercontrol. The children with undercontrolled temperament at 3 years of age were more than twice as likely to evidence disordered gambling at ages 21 and 32 than were children who were well-adjusted at age 3. These associations could not be explained by differences in childhood IQ or family socioeconomic status. Cleanly demonstrating the temporal relation between behavioral undercontrol and adult disordered gambling is an important step toward building more developmentally sensitive theories of disordered gambling and may put researchers in a better position to begin considering potential routes to disordered-gambling prevention through enhancing self-control and emotional regulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".