Beyond E-waste: Kenyan Creativity and Alternative Narratives in the Dialectic of End-of-Life
Bibliographic record
Abstract
The main focus of green IT campaigns and policy interventions in developing regions has been on efforts to counter the flows of e-waste coming from the West. This paper argues that while such interventions are necessary, they often fail to acknowledge the complexity of information-technological developments across the global South. Complementary narratives can uncover a more nuanced perception of the role played by second hand ICT equipment in development. E-waste is at first contextualized within the wider debate on the contested role of technology in post-development. Examples of the multi-dimensional role of technolog in development initiatives in Kenya are used to provide evidence of existing cultures of reuse and of their potential to inform and influence a shift in Western ICT consumption patterns, in line with contemporary debates on de-growth. Examples of alternative approaches to development in the context of ICT abound, and it's key to focus on those that have roots in the creation of value right where others would see only waste – translating the ethos of the grey economy in projects that reclaim economical and educational spaces.
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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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| 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".