Music listening, coping, peer affiliation and depression in adolescence
Bibliographic record
Abstract
This study was conducted with 418 French-Canadian adolescents from Montréal (Canada) and had three objectives: (1) to find empirical evidence that music listening in adolescence can lead to peer affiliation based upon music preferences; (2) to find out whether three styles of coping by music listening (original self-report scale: emotion-oriented, problem-oriented, and avoidance/disengagement) are related to depression levels in adolescence (French version of the Beck Depression Inventory: Bourque & Beaudette, 1982); (3) to examine whether peers' depression levels and coping by music listening are moderators of the relation between Metal music preference and depression levels in adolescent girls. The results of a peer nomination procedure indicated that music preferences and depression levels of participants are related to those of their peers. In girls, problem-oriented coping by music listening is linked to lower depression levels, whereas avoidance/disengagement coping by music listening is linked to higher depression levels. In boys, emotion-oriented coping by music listening is linked to higher depression levels. Finally, Metal music listening is related to higher depression levels in girls only if they affiliate with peers that are more depressed. The implications of the research regarding the music listening and psychosocial development and adjustment in adolescence are 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".