When the State Imposes the “Commons”
Bibliographic record
Abstract
After the brown bear reintroduction program was launched in the Pyrenees in 1996, the French and Spanish States fostered and funded a regrouping policy to protect the sheep flocks from the bear attacks. Drawing on a comparative analysis between two Catalan districts in north-eastern Spain (Val d'Aran and Pallars Sobirà) and the Ariège district in south-western France, this article scrutinises the extent to which the transformation of shepherding practices induced by the renewed presence of bears can be deemed as a return of the ‘commons’ to the Pyrenees. The emergence of public regrouped herds resembles an old and until then abandoned pastoral format, the communal herd. However, this iteration of collective action is promoted and tightly controlled by the State, whereas previously, local farmers used to manage the old communal system themselves. The regrouping policy mimics the morphology of locally generated models following historical property rights logic, while incorporating a modern form of public governmentality. The conceptualisation of property as a bundle of rights and the two ethnographic studies serve to critically engage with the notion of the commons and their return. The literature on environmentality and territorialisation allows us to read this State-driven policy through the lenses of imposition and dispossession.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".