Bibliographic record
Abstract
Consumer electronics design is an easily relatable and fast-cycling field of interest to students of all kinds, but particularly to those studying information science. Within this field, the e-waste problem is a significant ethics issue. Why does the logic of using computers involve the repeated purchasing and consumption of new machines, or “molded plastic epics” (Gabrys, 2011), and their significant manufacturing expenditure of carbon? Thinking back on calculating devices which supported problem-solving and this ethical problem of repeated consumption, the simple solar calculator stands out for its durability. The reason may be the initial sustainability design: early calculators, like more recent Citizen Eco-Drive watches, use a solar ambient-energy harvesting strategy that doesn’t store electricity in batteries; consequently they are very long lasting and low maintenance. As there are very few energy-harvesting electronics devices in the market reflecting emerging green narratives of degrowth, reuse, and upcycling, this research paper reviews the history and design of some of these rare devices while discussing their energy experience design strategies in the context of modern consumer electronics. I also present a series of speculative prototypes which feature broad affordability, openness, and a more ethical consumption ethos as discussion artefacts for design education students engaging with this problem.
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.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".