Reading note on Jean-Benoît Zimmerman: Les Communs. From shared gardens to Wikipedia [Les Communs. Des jardins partagés à Wikipédia (par Jean-Benoît Zimmerman)]
Bibliographic record
Abstract
In this book, the author, an economist at the CNRS, gives us his analysis of a contemporary debate opened by the Malthusian position of Garett Hardin, who denounced in Science in 1968 the tragedy of the of which ecological resources can be the victim, a problem already identified by Aristotle and presented by William Forster Lloyd, a proto-Marginalist economist, who supported the possibility of the destruction of the common prairie through overgrazing in an essay on population control published in 1833. These theses were taken up for application to fisheries management by Scott Gordon, a Canadian economist who promoted the system of individual fishing quotas. The book concludes with the necessary evolution of the law so that the commons can become a motor for change in our contemporary societies, undoubtedly through a democratic debate that will make it possible to establish the institutional framework for the deployment of the commons for a more united republic. The author therefore calls for the creation of a genuine political economy of the commons to reweave the social fabric and counterbalance the excesses of a capitalism that is now unbridled on a global scale.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".