Experiencing the landscape: landscape agency in a multifunctional valley after dam removal on the Sélune River, France
Bibliographic record
Abstract
Here, we examine landscape as an actor of ecological restoration projects rather than as a resource. Based on relational thinking and the notion of agency, we aim to identify affordances recognized by local actors and to mobilize relational thinking to understand human-river relations. Although restoration projects have mainly been tackled from the point of view of contestation and landscape attachment, we question the capacity of these operations to produce multifunctional landscapes. We analyze the way in which the radical transformation of a landscape, resulting from the removal of two hydroelectric dams, led stakeholders to act. Our results not only reveal the limits of engineering approaches that struggle to overcome the nature–culture dualism, but also the value of integrating non-humans when we consider relationships rather than only objects. We analyze how the potential uses of a valley are revealed by the radical landscape transformations brought about by an ecological restoration project. We observe how the stakeholders project themselves into this new configuration, the resulting landscape visions it inspires in them, and how new functions emerge from the relationships woven between a new landscape and its stakeholders.
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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 | 0.001 | 0.001 |
| 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 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".