Use of Electronic Mail by Educated Older Adults in Oyo State, Nigeria
Bibliographic record
Abstract
This study presents preliminary findings on the use of e-mails by educated older adults in Nigeria-based areas of residency. This study is based on a quantitative survey (n = 167) which investigated the level of awareness and use of e-mails, reasons for use and non-use, as well as continuance and intention to use e-mail by older adults in three settings (urban, semi-urban, and rural areas) of Oyo state, Nigeria. A questionnaire was used to collect data. Results showed that about half of the educated older adults were aware of e-mail with a higher percentage of those aware residing in the urban area. There was a low level of usage of e-mail, especially among the semi-urban and rural dwellers. The major purpose of using e-mail was to receive alerts for banking transactions. E-mail users at the three locations intended to continue using e-mail, although the intention was stronger among the semi-urban and rural dwellers. Most non-users in the semi-urban and rural locations were not aware of e-mail, while most did not use e-mail because they had alternative means of communicating with people and saw no need for it. Concerns about the security of e-mails, lack of awareness of the benefits of using e-mail, and lack of literacy in e-mail use are some other reasons for non-use. Most of the non-users had the intention to use e-mail in the future, especially those in urban and semi-urban areas. It is recommended that efforts be geared towards creating more awareness about the importance of e-mail among the older population as well as developing training interventions on the use of e-mail, especially among the semi-urban and rural dwellers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".