Kropotkin and International Relations: Challenging Ontological Narratives
Bibliographic record
Abstract
This project will utilize Peter Kropotkins theory of Mutual Aid to reconsider ontology in IR. Mutual Aid Theory holds that the evolution of organisms is shaped by cooperation within a group of species against a variable ecology; thus giving rise to a sociality instinct (Kropotkin 1902). This is in stark contrast to the Malthusian assumption that evolution takes place at the individual level according to their intraspecific fitness. Mutual Aid Theory, applied to the realm of politics, overturns collective action problem-grounded theories that hold that the egoistic and competitive drive of humans must be overcome to promote cooperation. Thayer (2004) applied the orthodox individual-fitness interpretation of evolution to shore up Realist arguments. This study will respond to Thayers approach by juxtaposing it against Mutual Aid Theory, and augmenting this with empirical evidence accumulated in the life science fields. A scientific realist approach, placing analytical priority on ontological investigations over epistemological/methodological assumptions, is employed to assist in the criticism of orthodox reductionist ontologies. However, equally in line with Kropotkins ideas, this scientific realist approach also provokes ontologically-driven inquiries into post-sovereignty global politics.
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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.013 | 0.028 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".