A CRITICAL PERSPECTIVE ON CURRENT MODELS OF INTERGENERATIONAL LEARNING
Bibliographic record
Abstract
Research into different aspects of intergenerationalities continues to develop at a considerable pace for individuals, communities, and society. Multiple practices for older people are organized around the presumed benefits of intergenerational interaction, with intergenerational programming operating as a taken-for-granted practice. However, the merits of this approach, the models that inform practice, and the learning that takes place between older and younger people, remain under-theorized. This paper discusses dominant theoretical frameworks including developmental and psychosocial models of intergenerational learning such as the Social Cognitive Learning model, and the Life Span approach (Erikson 1963; VanderVan, 2011). It documents how the field of intergenerationality is conceptualized in the realms of learning; how models retain age and stage based assumptions, including the polarizing discourses of ‘decline’ and ‘activity’. By understanding the underlying assumptions of intergenerational learning, this paper makes an important contribution to the theoretical foundations that are required to build intergenerational landscapes.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".