Adolescents in Divorcing Families
Bibliographic record
Abstract
A representative sample of 3,198 Canadian adolescents in grades 6 through 12 was surveyed about seeking help in the face of parental separation and divorce. Qualitative content analyses of adolescents' responses to open-ended questions were used to identify themes that were reliably coded. In terms of “best” help-seeking options for adolescents in divorcing families, adult counsellors and friends were most frequently endorsed a total of 18 options generated by teens. When questioned about what helps youths to access the help they need, 11 themes emerged; peer support, a generally supportive environment, personal recognition of the need for help, a teen's personal strengths, and family support were most frequently mentioned. Obstacles to getting help were also coded into 11 reliable themes; feelings of being flooded or overwhelmed by negative feelings about the divorce, negative peer consequences, negative view of help options, psychological denial, and negative family influences were most frequently cited. Finally, an analysis of adolescents' overall psychological attitudes towards help-seeking revealed an optimistic/trusting outlook among the strong majority of respondents. A brief analysis of the types and helpfulness of past help-seeking attempts was presented. Sex-related, age-related, and experience-based differences in the adolescents' responses were considered, and implications of the findings for practice and research were discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".