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
Big Tech supports social media, the stock market, insurance companies, scientific research, financial transactions, mass surveillance and monitoring, the ‘Internet of things’, ‘smart city’ sensors and grids, and mobile communications for Internet users writ large. By most industry accounts, data centres – and the cloud infrastructure that undergirds it – has become the most important sociotechnical system of our time, but also the least sustainable. Interestingly, one of the alternatives to these water- and energy-intensive data storage solutions has emerged from advancements in synthetic DNA technologies, now touted by the industry as a safer, greener and more efficient alternative. But how did we get here? How might ideas of 'sustainability' and 'efficiency' function in this context? In conversation, Mél Hogan and Deb Verhoeven discuss the idea of ‘Sustainable DNA’ – in its various instantiations – as an object of critical media studies.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.070 | 0.001 |
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