Subjective age in early adolescence: Relationships with chronological age, pubertal timing, desired age, and problem behaviors
Bibliographic record
Abstract
Subjective age generally refers to the age that one feels. In a cross-sectional questionnaire study of 245 adolescents ages 10-14 years, we examined (a) whether, and when, a cross-over in subjective age occurs, (b) differences in subjective age among pubertal timing groups, (c) correlations between subjective age and each of desired age and five problem behaviors, and (d) the relative contributions of chronological age, pubertal timing, desired age, and problem behaviors to subjective age in boys and girls. Adolescents generally reported subjective and desired ages that were slightly older than their chronological ages. A cross-over in subjective age occurred at 10.4 years. Late maturing adolescents reported relatively younger subjective ages than their early and on-time maturing peers. For boys, only desired age significantly predicted subjective age. For girls, an older desired age, late maturation, and higher scores on anxious/depressed feelings, rule-breaking behavior, and aggressive behavior significantly predicted older subjective ages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".