Agents of Technology Localization in East Africa: Case Studies of Social Enterprises in Tanzania
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technology localization refers to activities that seek to make particular technologies locally functional and locally embedded in order to overcome resistance to their adoption. These activities can be described as diffusion, institutional support, and technical adaptation. In developing societies that face experiences of resistance to technological change, several organizational agents could serve as agents of localization. This paper showcases a number of social enterprises in East Africa – particularly in Tanzania – that are involved in localizing technologies for sustainable energy and agricultural mechanization. Field data were collected between December 2014 and September 2015. Staff, clients and partners of the social enterprises were interviewed. In addition, field observations and a scan of accessible reports and documents of social enterprises and their partner organizations took place. The cases demonstrate technology localization activities and assess the effectiveness of these social enterprises as agents of localization. The study concluded that, given appropriate tools and context, such as engaging early adopters of innovation and staying attuned to feedback from local communities, social enterprises can be effective agents of technology localization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it