A radical relational agency: Foucault, complexity theory and environmental resistances
Bibliographic record
Abstract
The aim of this thesis is to examine a radical relational agency, applied to contemporary environmental resistances, that incorporates both the thought of Michel Foucault and complexity theory. While Foucault’s thought, following from his argument that power is a relation, implies a relational agency, it does not, however, account for the agency of nonhumans and environments. Because power is a relation and not a possession, it can no longer be viewed as an attribute of individual subjects. Similarly, a relational agency is defined as an aspect of power relations. Complexity theory, on the other hand, acknowledges that humans interact with nonhumans and environments, but does not acknowledge that all relations are relations of power. In addition to Foucault’s explanation of power relations, complexity theory explicitly describes the processes of self-organization through which individual and diverse agents interact and change can emerge. Thus, a radical relational agency is defined as an aspect of the power relationships between many diverse agents. Change, according to both Foucault and complexity theory, happens nonlinearly. As a result, it often occurs unpredictably. However, change within complex systems is also limited by previous historical emergences. In this sense, both possibility and risk are inherent in the relationships between humans, nonhumans and environments. Indeed, I argue that a radical relational agency occurs because there are both possibilities and risks generated within ecological relations and relations of power. Therefore, I argue that any environmental action must account for the unpredictability inherent to the complex interactions between humans, nonhumans and environments.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.046 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 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".