Understanding the Potential of Intergenerational Collaboration
Bibliographic record
Abstract
Our relationship with younger and older generations in our lives can facilitate our need for personal care, material security as well as our search for identity and belonging. Biggs [2007] describes how understanding relationships between generationslies at the heart of society’s contemporary dilemmas yet in the social sciences, it remains to be a relatively under explored lens to understanding processes of change [Biggs, 2007, p. 695]. The following research gathered existing literature that discusses intergenerational relations in the domains of a) Sociology and b) Social Gerontology. The sociological tradition discusses processes of social change or how significant historical events shape the environment we age in while the Social Gerontological tradition examines social structures that organize activities across the life course. \n \nUsing Suhair Inayatullah’s Causal Layered Analysis as a framework, the following research deconstructed a projected trend of rising demographic dependency in Canada to understand its systemic causes, world views and metaphors. The “assembly line of aging” is revealed as a metaphor that describes a rigid system of age specialization, based on the standardization of activities across the life course. However, as changes in demography, lifestyle and lifespan continue to transform, the assembly line of aging is argued to be too rigid to adapt to the needs of future generations. The “meandering river” is introduced as an alternative metaphor that has the potential to work with and balance a rigid system through recognizing age heterogeneity and challenging conventional age specializations. In order to so, enablers and key stakeholders are highlighted to address the issue more systemically by representing opportunities for agency and action at the individual, community, organizational, and policy level. Finally, this project suggests that a) celebrating age diversity, b) nurturing intergenerational empathy and c) collaborating towards sustainable futures have the potential to enable futures of intergenerational knowledge creation.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.014 | 0.028 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".