Bibliographic record
Abstract
The concept of the Anthropocene draws attention to human activity's impact on the planet at the geological scale. It is tempting to reason that like evolution, a heliocentric solar system or quantum mechanics, climate science compels us to accept as real a radical new ontology, the ‘anthroposphere’, with far-reaching social and political consequences. I wish to argue that this temptation should be resisted. The Anthropocene cannot be understood entirely as a natural scientific phenomenon, although it can be treated as such for certain purposes. It is also an irreducibly social phenomenon. This is not to say that it is a socially constructed concept like nationhood, but that it is constituted by natural causal processes that are irreducibly entangled with social causal processes. Adopting the Anthropocene as a working concept therefore requires that we understand the causal processes involved in bringing it about as social causal processes, while also viewing these processes as objectual, open to public scrutiny and capable of compelling public assent. Social causes are not, however, easily subjected to such a naturalistic treatment. I conclude that the Anthropocene is not currently a suitable candidate for inclusion in a naturalist ontology.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".