The Utility of Brief Mattering Subscales for Adolescents: Associations with Learning Motivations, Achievement, Executive Function, Hope, Loneliness, and Risk Behavior
Bibliographic record
Abstract
The current study examined the feasibility of adapting an existing measure to create a brief mattering measure suitable for use with adolescents. We then evaluated this brief measure by testing the hypothesis that mattering in adolescents is associated broadly with positive achievement outcomes and associated motivational orientations and behavioral tendencies. A sample of 206 high school students completed a slightly modified version of the Mattering Index, the Pattern of Adaptive Learning Scales, and a measure of executive function. School grades, school risk behavior, and social risk behavior were also assessed. Participants also completed measures of hope and loneliness. Psychometric analyses resulted in two brief four-item mattering subscales tapping a) general mattering and b) mattering by giving value to others. Correlational and regression analyses established that both mattering factors were associated with a positive academic orientation and higher grades. Mattering was also associated with less risk behavior, lower levels of loneliness, and higher levels of hope. Gender differences were found in terms of levels of mattering and the correlates of mattering. The findings are discussed in terms of how a focus on the promotion of mattering should contribute to an adaptive academic orientation, enhanced self-regulation, and the capacity to be adaptable and resilient.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".