A Social-Media Study of the Older Adults Coping with the COVID-19 Stress by Information and Communication Technologies
Bibliographic record
Abstract
Abstract In this paper, we convey the results of our digital fieldwork within the current mediascape (English) by examining online reactions to an important source of cultural influence: the news media's depiction of older adult's stress, the proposals offered to older adults to assist them in coping with the stress of living in the COVID-19 pandemic, and finally, the responses of online commentators to these proposals. A quasi-automated social network analysis of 3390 valid comments in seven major international news outlets (Jan-June 2020), revealed how older adults were generally resourceful and able to cope with COVID-19 stress. For many in this technology-using sample, information and communication technologies (ICTs) were important for staying informed, busy, and connected, but they were not the primary resources for coping. Although teleconferencing tools were praised for facilitating new forms of intergenerational connection during the lockdowns, they were considered temporary and inadequate substitutes for connection to family. Importantly, older adults objected to uncritical and patronizing assumptions about their ability to deal with stress, and to the promotion of ICTs as the most important coping strategy. Our findings underline the necessity of a critical and media-ecological approach to studying the affordances of new ICTs for older adults, which considers changing needs and contextual preferences of aging populations in adoption of de-stressing technologies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".