Adaptation and Validation of the Life Events and Difficulties Schedule for Use With High School Dropouts
Bibliographic record
Abstract
The Life Events and Difficulties Schedule (LEDS) is considered the standard for measuring psychosocial stressor exposure, but it has not been used with academically at-risk adolescents, including high school dropouts. The goal of this study was to (1) adapt the LEDS for use with this population, and (2) examine the reliability (interrater) and validity (concurrent and predictive) of this adaptation among a sample of vulnerable adolescents (N = 545). Good reliability coefficients (.79-.90) were obtained, and stressor exposure was associated with concurrent criteria indexing mental health outcomes (depression) and major risk factors for dropout (administratively recorded and self-reported). Also, LEDS scores predicted dropout beyond these risk factors. The adapted LEDS appears useful for describing academically struggling adolescents' stressor exposure.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".