Trends in adolescent research for the new millennium
Bibliographic record
Abstract
This article highlights several promising trends in research on adolescence and discusses the likely future course of several recent developments in adolescent research. Current trends include a focus on the transition to young adulthood, the increasing examination of the context and co-occurrence of adolescent problems, and emphasis on the resilience of adolescents in high-risk circumstances. There is a strong need for more research on the cognitive and neurocognitive gains and changes of adolescence and on positive psychosocial behaviours and outcomes for youth. We are just beginning to understand within-group differences in adolescent development, including the life experiences of minority youth, adolescents with disabilities, and homosexual adolescents. The impact of social context and social change on adolescents is also receiving more attention. Methodological approaches likely to be seen more in the future include the use of pattern-centred analyses to complement traditional variable-centred approaches and a greater appreciation for qualitative data analysis as a route to gaining insights into adolescent development. Finally, university-community partnerships are promoted as a way to solve the problems of youth and improve the probability of their healthy futures.
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 | 0.030 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".