Shadowing the Anthropocene: Eco-Realism for Turbulent Times
Bibliographic record
Abstract
A spectre is haunting humanity: the spectre of a reality that will outwit and, in the end, bury us. “The Anthropocene,” or The Human Era, is an attempt to name our geological fate – that we will one day disappear into the layer-cake of Earth’s geology – while highlighting humanity in the starring role of today’s Earthly drama. In Shadowing the Anthropocene, Adrian Ivakhiv proposes an ecological realism that takes as its starting point humanity’s eventual demise. The only question for a realist today, he suggests, is what to do now and what quality of compost to leave behind with our burial. The book engages with the challenges of the Anthropocene and with a series of philosophical efforts to address them, including those of Slavoj Žižek and Charles Taylor, Graham Harman and Timothy Morton, Isabelle Stengers and Bruno Latour, and William Connolly and Jane Bennett. Along the way, there are volcanic eruptions and revolutions, ant cities and dog parks, data clouds and space junk, pagan gods and sacrificial altars, dark flow, souls (of things), and jazz. Ivakhiv draws from centuries old process-relational thinking that hearkens back to Daoist and Buddhist sages, but gains incisive re-invigoration in the philosophies of Charles Sanders Peirce and Alfred North Whitehead. He translates those insights into practices of “engaged Anthropocenic bodymindfulness” – aesthetic, ethical, and ecological practices for living in the shadow of the Anthropocene.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".