The Ends of the World: International Relations and the Anthropocene
Bibliographic record
Abstract
The concept of the Anthropocene – the geological epoch defined by human action – has so far remained largely absent from International Relations (IR) analyses. This is perplexing given the monumental stakes involved in dealing with planetary change and the discipline’s overriding focus on crisis. This silence may exist, however, because contemporary studies of international relations are troubled by the Anthropocene, which shifts basic assumptions about how humans live in the midst of perpetual danger, harm, and risk. It also presents us with the prospect of failure in existential terms, if indeed we are living in (and causing) ‘the sixth mass extinction’. The focus of this article, therefore, is threefold. First, to consider the challenges to environmental IR that the Anthropocene concept presents; second, to probe what it means for IR to respond to the end of nature; and third, what is required of IR to deal with the prospect of mass extinction. It is argued that Earth system changes wrought by human action require the discipline to demystify its own ontological, epistemological, and ethical approaches that are culpable in ushering in the Anthropocene. Doing so may allow IR to provide necessary insight into the contemporary and historical effects of the state system as an enabler of planetary change, and the future possibilities for global politics within 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.022 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".