Prospects of PPP in Expanding ICT Services in Rural Bangladesh: A Case of Union Digital Center
Bibliographic record
Abstract
ICTs have appeared to be one of the driving factors of modern economic growth with multilayered impacts on different aspects of the economy and society particularly in developing countries. However, due to infrastructural bottlenecks and huge initial investment requirements, although public and private sectors have been working with their respective motives, a vast majority of population in Bangladesh especially in the rural areas still do not have functional access to internet facilities and digital services. On the above backdrop, based on the survey of secondary sources of information, this paper attempts to review the prospects of public private partnership in expanding ICTs and digital services in rural Bangladesh and as to what extent it contributes to reducing digital divide and achieving broader development objectives. Drawing from the experiences of other developing countries and thoroughly taking into account the case of union information and service centers in Union Parishad level in Bangladesh, this paper makes it evident that neither pubic nor private bodies can render the poor and rural people the access to digital services in a segregated manner except without a joint endeavour or partnership for good. It is emphasized that PPP can be a viable option in expanding digital internet services to the poor and marginalized population in rural Bangladesh.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".