The Evolution of an ICT Platform-Enabled Ecosystem for Poverty Alleviation: The Case of Ekutir1
Bibliographic record
Abstract
This paper analyzes the pioneering work of eKutir, a social business in India that leverages an information and communication technology (ICT) platform to progressively build a self-sustaining ecosystem to address multiple facets of smallholder farmer poverty. The study reveals that eKutir’s ecosystem has evolved through five distinct phases, each expanding the number and type of actors engaged and the breadth of ICT-supported services provided. The evolution displays a distinct pattern where the five elements of the ecosystem progressively evolve and reinforce one another to create a system that is economically sustainable, scalable, and can accelerate transformative change. The study has important implications for the design of emergent ICT platforms, which can enable an ecosystem-based approach to address complex problems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".