Inclusive Capitalism and Development: Case Studies of Telecenters Fostering Inclusion Through ICTs in Bangladesh
Bibliographic record
Abstract
Lack of sustainable approaches for public access venues like telecentres have led to the emergence of several entrepreneurial and market-driven models of telecentres in developing countries that are driven by multinational corporations, governments and social enterprises. This phenomenon falls under the rubric of inclusive capitalism which argues that in the contemporary socioeconomic context, private investment and entrepreneurial activities are crucial for economic growth and job creation in developing countries. In this paper, I undertake three case studies of telecentres in Bangladesh: a private sector enterprise developed and operated by a multinational corporation, a social enterprise, and a public-private partnership. The case studies combine review of organizational documents as well as analysis of survey data from the ‘ Global Impact Study of Public Access to Information & Communication Technologies’. While a common feature in all three of the cases is the reliance on market mechanisms to provide affordable ICT services to the poor, the findings highlight how in some cases the initiatives approach the issue of ‘inclusion’ differently. The paper illustrates the convergence in thinking among various institutional domains of development about the indispensability of inclusive capitalism approaches to bring about socioeconomic development through ICTs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".