Nature without Borders: Art and Ecological Resistance in Silvia Cini’s <i>Avant que nature meure</i>
Bibliographic record
Abstract
Contemporary ecological art increasingly attempts at rematerialising the numerous ‘borders’ invisibly contributing to the stories of environmental violence of the ‘Anthropocene.’ In this perspective, Silvia Cini’s interdisciplinary initiative Avant que nature meure (2015–2024) aims at exposing the entanglement of the main “borders” perpetuating human exceptionalism and its destructive consequences on the environment—i.e. the enclosure and exploitation of nonhuman life for human profit, as well as racial and gender domination. By intersecting visual, political, and legal tactics—spanning from the creation of a participatory repository of urban flowering sites to neo-situationist dérives, public gatherings, workshops, and museum exhibitions,—Cini advocates an interventionist and community-based approach to art as a means of direct action and social transformation. In fact, the recognition (both in visual and political terms) of orchids’ resilience in a man-altered landscape discloses, in the artist’s intention, alternative forms of coexistence to the ecocidal, neocolonial, and hetero-patriarchal apparatus, envisioning a radical renegotiation of hegemonic relations of (in)visibility.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".