Trust and Technology Repair Infrastructures in the Remote Rural Philippines
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
This paper analyzes the processes and challenges of technology repair in remote, low-income areas far from standard ICT repair infrastructure. Our sites of study are the fishing and farming villages of Dibut, Diotorin, and Dikapinisan in Aurora Province, Philippines, located in coastal coves against a mountain range. Residents are geographically isolated from urban areas, with the nearest peri-urban center of Baler a boat trip of several hours away, infeasible in some sea conditions. Unlike prior work in more connected rural areas, there are no local repair shops and device repair is uncommon, despite frequent breakage due to harsh conditions for electronics. The scarcity of local electronics repair limits technology access and leads to accumulation of e-waste. While prior work demonstrates that local electronics repair capability does arise in many rural areas around the world, we must also acknowledge that the successful emergence of this infrastructure depends on the intersection of many structural conditions and cannot be taken for granted. We present the material hardships of achieving local repair in terms of seams between heterogeneous urban and rural infrastructures, which illustrate the cove communities' marginality with respect to many forms of public infrastructure. However, intermittent and informal repair infrastructures based on trust relationships emerge to patch these seams in remote settings. We show how trust affects the way people dynamically construct repair infrastructure and why, based on their remoteness and the resulting value propositions of repair. Networks of trust between repairers, their clients, suppliers, fellow repairers, and certifying or training institutions crucially facilitate the movement of resources and expertise across the Philippines, but also reinforce the marginality of residents and repairers in the coves. Despite these structural challenges, local people are able to maintain a robust ecosystem for rural electrical line repair, from which we generalize the model of training grounds as a strategy for sustaining local communities of repair experts.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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