Going Beyond Telecenters to Foster the Digital Inclusion of Older People in Brazil: Lessons Learned from a Rapid Ethnographical Study
Bibliographic record
Abstract
Telecenters take on a prominent role within the current information and communications technology (ICT) ecosystem in Brazil. They are seen by a great many as a key means to foster the digital inclusion of the older population in the country. This paper draws upon a rapid ethnographic study conducted with 78 older people in a center that teaches computer classes to seniors in Brazil. The results show that providing older people with technological infrastructures is not enough to strengthen their digital inclusion if their basic and non-instrumental needs are not taken into consideration in defining educational activities to be carried out in public centers. Participants’ basic needs when it comes to interacting with ICT, such as coping with accessibility issues, were dynamic, whilst non-instrumental needs, fulfilled by using these technologies, such as interacting with relevant others, remained fairly constant throughout the study. Drawing on the results of the study, strategies for fostering the digital inclusion and well-being of older people in Brazil that go beyond telecenters are suggested.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".