Life-Span Learning: A Developmental Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The article discusses learning as embedded processes of development and aging, and as social activity over the life course. The concept of life-span learning is proposed and outlined to discuss these processes as aspects of and propositions in life-span development and aging theory. Life-span learning processes arise and continuously develop in a dynamically complex body, brain, and the mind they support as essential features of development and aging over the life course. Life-span learning processes are established by evolutionary adaptive mechanisms, enriched by challenging environments, and continuously developed in supportive social structures. These ideas are derived from evolutionary biology and psychology, the cognitive sciences, life-span development and aging research, and adult development and learning studies. It is argued that life-span learning activities that challenge the body-mind-brain nexus are indispensable to optimize individual development and aging. Three global interventions and their strategies are discussed that enhance life-span learning: Learning to Learn, Learning for Growth, and Learning for Well-being.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it