Intergenerational Aid in the 21st Century
Bibliographic record
Abstract
As digital immigrants of the 21st century, the current elderly always seem to have difficulty catching up with today's technologies. When day-to-day services like banking, healthcare, travel, etc., become entirely digitized without giving seniors the required time, education, or support to get on board, it gradually chips at their independence, dignity, and agency. To keep afloat in this rapidly digitizing world, most seniors find themselves relying on assistance from the people around them, such as younger family members, neighbors, friends, and community volunteers. This research explores the various facets and multitudes of digital support that younger persons commonly provide seniors. What factors influence this intergenerational digital support between seniors and younger generations? What is the role of technology and its design in this context? Through qualitative interviews and participatory workshops, this thesis delves into the perspectives and lived experiences of various stakeholders like seniors, younger generations, community volunteers, tech coaches, etc. The research is also fundamentally informed by my experience as a regular volunteer at the West End Seniors' Network, an NGO offering social and community support for seniors in Vancouver. After a thorough thematic analysis of the data gathered, the paper derives key insights about intergenerational digital support under the following themes - (1) A Generational Divide, (2) The 'Why,' (3) The 'How,' (4) Benefits, and (5) Barriers. With these insights, the research attempts to situate the role of intergenerational aid in the broader picture of digital inclusivity for seniors. Intergenerational support is only a facet of this wicked problem; other stakeholders like family, community, government, private companies, etc., also share responsibility in keeping seniors apace with the digital world. This research is then applied to cohesively map out potential best practices for multiple stakeholders to improve digital literacy for seniors. However, while this is a more significant systemic change proposed for the long run, we could now take small steps and solutions to contribute towards the larger goal, like capitalizing on the benefits of this already widespread intergenerational digital support. In light of this, a mobile application is designed and prototyped to facilitate digital aid between seniors and younger persons with ease, efficiency, and warmth.
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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 | 0.000 |
| 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) | 0.000 | 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".