Vibrant Rock, Earth, and iPhone: Disrupting Extractivism in the Work of \nMarcela Armas and François Quévillon.
Bibliographic record
Abstract
As new extractive frontiers emerge in the Anthropocene, this thesis examines the way artworks by Mexican artist Marcela Armas and Canadian artist François Quévillon intervene in the capitalist paradigms, worldviews, and technologies that enable the extraction and exploitation of nature, mineral resources, and human labour. Tsinamekuta, 2016-2021, by Armas stands as a defence against mining practices on Indigenous land in Mexico, and revolves around a magnetic mineral called pyrrhotite and its radical potential to hold Earth memory. Esker/Lithium, 2019-2024, by Quévillon enters an iPhone into dialogue with a controversial prospecting lithium mine in Quebec, and considers the way novel forms of extraction emerge within digital, technological, and information-saturated environments. These artworks cultivate an ecology of practices that navigate assemblages of technologies, extractive zones, and environments across varied topographies of power. The theoretical foundation for this thesis draws from Elizabeth Povinelli’s concept of geontopower, Jason Moore’s inquiry into capitalism as an earth-moving and environment-making process, Vanessa Watt’s Place-Thought, and Franco “Bifo” Berardi and Jean Baudrillard’s ideas around semiocapitalism and simulacrum, amongst other authors. These thinkers investigate the climatic and social catastrophe of our epoch and challenge the ways in which dominant strategies of power dictate relations to nonhuman entities and to nature. This thesis thus explores what it means to be attentive to, become-with, and form alliances with different forms of existence through artistic practice, offering ways to move forward within the precarious and challenging times known as the Anthropocene.
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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 | 0.003 | 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 | 0.015 | 0.024 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".