School Disconnectedness: Identifying Adolescents at Risk
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: School connectedness, or the feeling of closeness to school personnel and the school environment, decreases the likelihood of health risk behaviors during adolescence. The objective of this study was to identify factors differentiating youth who do and do not feel connected to their schools in an effort to target school-based interventions to those at highest health risk. METHODS: The study population consisted of all students attending the 7th through 12th grades of 8 public schools. The students were asked to complete a modified version of the in-school survey designed for the National Longitudinal Study of Adolescent Health (Add Health). The school connectedness score (SCS) was the summation of 5 survey items. Bivariate analyses were used to evaluate the association between SCS and 13 self-reported variables. Stepwise linear regression was conducted to identify the set of factors best predicting connectedness, and logistic regression analysis was performed to identify students with SCS >1 standard deviation below the mean. RESULTS: Of the 3491 students receiving surveys, 1959 (56%) submitted usable surveys. The sample was 47% white and 38% black. Median age was 15. Median grade was 9th. The SCS was normally distributed with a mean of 15.7 and a possible range of 5 to 25. Of the 12 variables associated with connectedness, 7 (gender, race, extracurricular involvement, cigarette use, health status, school nurse visits, and school area) entered the linear regression model. All but gender were significant in the logistic model predicting students with SCS >1 standard deviation below the mean. CONCLUSIONS: In our sample, decreasing school connectedness was associated with 4 potentially modifiable factors: declining health status, increasing school nurse visits, cigarette use, and lack of extracurricular involvement. Black race, female gender, and urban schools were also associated with lower SCS. Further work is needed to better understand the link between these variables and school connectedness. If these associations are found in other populations, school health providers could use these markers to target youth in need of assistance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.013 |
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 it