The Socioecological Fix: Fixed Capital, Metabolism, and Hegemony
Bibliographic record
Abstract
This article, the second of two, argues that conceptualizing the socioecological fix involves understanding how fixed capital, as a produced production force, can transform the socioecological conditions and forces of production while also securing the hegemony of particular social hierarchies, power relations, and institutions. We stress that fixed capital is inherently political–ecological in its constitution and how it shapes socioecological processes of landscape transformation. Fixed capital necessarily congeals socioecological materials and processes and can be understood as a produced form of nature tied to the circulation of value and the deployment of social labor. Fixed capital is therefore inherently metabolic and internalizes and transforms socioecologies. We also discuss the fixing of capital within socioecological landscapes as processes involving both the formal and real subsumption of nature. We emphasize the dual role of fixed capital formation in shaping the socioecological conditions and forces of production and, more broadly, of everyday life. Thus, we argue, fixed capital formation as a metabolic process cannot be fully conceptualized in narrowly economic terms. We turn to Gramsci and some recent work in political ecology to argue that socioecological fixes need to be understood in ideological terms and specifically in the establishment and contestation of hegemony.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.059 |
| Scholarly communication | 0.008 | 0.012 |
| 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".