Readily available technologies in low-resource communities: a review and synthesis
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
Socioeconomic changes in recent years have forced a shift in focus from resource abundance to resource scarcity and from top-down solutions to bottom-up, community-driven solutions. Consequently, novel research has emerged on how resource-scarce communities innovate by leveraging readily available technologies that are more accessible and affordable than other technologies. This paper presents a scoping literature review on the role of Readily Available Technologies (RATs) in Low-Resource Communities (LRCs) and identifies knowledge gaps as well as future research opportunities. We analyzed 49 articles published in relevant, high-quality journals between 2010 and 2021. We propose a framework illustrating the interactions among RATs, community actors in LRCs, and contextual factors. Through a theoretical framework, this article raises awareness about how practitioners utilize RATs in various LRC contexts to facilitate community and economic development. It lays the foundation for future theoretical and empirical development and provides guidance to practitioners for fostering RAT-driven community development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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