ASSESSMENT OF RISK AND PROTECTION IN NATIVE AMERICAN YOUTH: STEPS TOWARD CONDUCTING CULTURALLY RELEVANT, SUSTAINABLE PREVENTION IN INDIAN COUNTRY
Bibliographic record
Abstract
Background: This study constitutes a building block in the cultural adaptation of Communities That Care (CTC), a community-based prevention system that has been found to be effective in reducing youth problem behaviors. Methods: Using the data from the CTC normative survey dataset that consists of more than quarter million youth nationwide, this study examines the reliability and validity of scores derived from the Communities That Care Youth Survey (CTC-YS), one of the primary assessment tools for gathering community data on risk and protective factors related to problem behaviors including substance use. The reliability and criterion validity analyses are conducted overall for the nationwide sample of youth as well as for the student subsample of Native American youth. Results: The results of this study indicate that the existing CTC-YS assessments of risk and protective factors in the domains of community, family, school, and peer groups as well as within individuals yield scores that are reliable and valid within the Native American sample of youth. Conclusions: This study informs the third step in the CTC prevention planning process, which involves the assessment of risk and protective factors to be targeted in preventive interventions. The question of how the assessment of risk and protective factors among Native American youth might be further improved and a description of efforts related to the cultural adaptation of the CTC program currently underway are also addressed in the discussion.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".