Bibliographic record
Abstract
Abstract The term, “cognitive aging,” is typically used to refer to the area of developmental psychology focusing on the study of cognitive changes from young adulthood to very late life. Among the developmental processes of interest are those that reflect cognitive functioning, such as intelligence, memory, and reasoning. An underlying assumption is that cognition is used in different ways to accomplish different goals throughout adulthood, but that it is always a central component of one's concept of self—past, present, and future—and one's adjustment to challenges of everyday life. This area of lifespan developmental research is a particularly active one, in that it is at the crossroads of both classic theoretical questions and important issues of individual and social application. In this chapter, we summarize selected leading issues in the field of cognitive aging. These include: (1) intelligence and patterns of intellectual aging, (2) differential profiles associated with the “aging” of various systems of memory, (3) new topics in such memory‐related domains as metamemory and social‐interactive memory, and (4) emerging research in such novel domains as wisdom, creativity, compensation, and plasticity. We conclude that, because cognitive aging involves developmental processes that range from the neurological through the individual to the social levels of analyses, it will continue for the foreseeable future to fascinate scholars and anyone else who is curious about how and why cognitive changes occur throughout adulthood.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".