Industrializing Bacterial Work: Microbiopolitics, Biogas Alchemy, and the French Waste Management Sector
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
Biological waste recycling has recently attracted widespread interest and investment. Large industrial plants that use microbiological engineering to process municipal waste and produce biogas have been established in different countries including Germany, France, Portugal, Brazil, Canada, and China, to name a few. These biowaste facilities are not simply classical energy infrastructures, as they are commonly described, but rather rely on the power of bacteria, archaea, and fungi at several levels to accomplish the work of waste metamorphosis. Such an appropriation of microbes’ vital force is based on specific and complex human–microbe relations, or microbiopolitics, that rely on practices of attention, care, and proximity with waste material. However, in these industrial attempts of upgrading the metabolic work of bacteria, the need for more hands-on daily care of waste materials and biological processes is being superseded by the automation of waste processing. Close examination of the French context shows that this shift produces ignorance regarding the growth and evolution of bacterial colonies and reduces humans’ attention and proximity to the industrial process, thereby depriving the microbes of elements that hitherto kept them domesticated.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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