Bibliographic record
Abstract
There has been very little research and policy regarding the inclusion of older adults in new technological applications in Nigeria and other sub-Saharan African region. The study examined the use of social media among older adults in Ibadan, South-West, Nigeria using a semi-structured interview. A qualitative explorative study was set-up, involving six consenting members of the Nigerian Union of Pensioners (NUP), Ibadan branch whose age is above 55 years. Purposive sampling technique was used to include the participants who have access to a social media-enabled phone. A semi-structured was conducted to obtain information about the social media usage among the older adults. Thematic analysis was used to analyze interview transcripts. The mean age of the older adults is 58.5. Two themes emerged from the interview session: experience and barriers to social media use. Participants had an exciting experience using social media to maintain social connectedness and barriers associated with privacy, poor access to the internet, illiteracy, and frustration. The study concludes that social media use is essential to sustaining social connectedness among older adults. Desire to use social media among the older adults is embedded in their social, personal, and cognitive context. The study advocates for inclusive digital programming for older adults.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".