Internet Access At Public Access Venues In A Developing Countries: Lessons from Yogyakarta, Indonesia
Bibliographic record
Abstract
This paper aims to present differences between male and female internet users in terms of their internet access, including the information they seek, their ICT uses, their frequency of use, and their barriers. This paper reports data from 400 internet café users in urban and non-urban areas in Yogyakarta, Indonesia.The results show that there were some differences between the male and female users. Firstly, the number of male users who visited in internet café was slightly higher than that of female users. Secondly, in terms of information the users seek, female users in urban areas were more interested in accessing education and health contents than male users, whereas in non-urban areas female users were more interested in educational contents and agricultural contents. Secondly, in terms of the ICT uses, male users in urban areas tended to have more interest in using ICT for e-commerce and business than female users. On the other hand, in non urban areas, female users tended to have a higher interest in using ICT for blogging/social networking than male users. Next, with regard to frequency of use, in both urban and non-urban areas male users visited an internet café more often than female users. Finally, in term of barriers in using ICT; the most serious barriers both in urban and non-urban areas were distance, cost, content and services.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.002 | 0.000 |
| 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; 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".