COMMONS-BASED AI: A SOCIOMETABOLIC CRITIQUE OF THE HEGEMONIC MODEL AND PATHS TO EMANCIPATION
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 article advances a sociometabolic critique of the dominant artificial intelligence (AI) paradigm and articulates a transformative proposal for Commons-Based AI. Here, “commons-based” goes beyond resource management or infrastructure sharing: following Dardot & Laval (2017), the Common (le Commun) is conceptualized as an instituting praxis—a dynamic, collective process of self-governance, co-production, and social emancipation. Thus, the article frames AI not merely as a good to be managed, but as a field for instituting new social relations, democratic governance, and emancipatory sociometabolic transition. The argument integrates Marxian, feminist, and Southern epistemologies with practical cases, proposing a triadic framework—collective memory, dialogic governance, emancipatory purpose—and concrete mechanisms for funding, validation, and global equity. The Kairós Protocol is presented as a pioneering method for reflexive, dialogical human–AI co-authorship. By connecting theoretical innovation to lived practice, the article demonstrates that reorienting AI as a Common is both feasible and urgent for societal transformation.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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