The transformation of provisioning systems from an integrated perspective of social metabolism and political economy: a conceptual framework
Bibliographic record
Abstract
Energy, food, or mobility can be conceptualized as provisioning systems which are decisive to sustainability transformations in how they shape resource use and because of emissions resulting from them. To curb environmental pressures and improve societal well-being, fundamental changes to existing provisioning systems are necessary. In this article, we propose that provisioning systems be conceptualized as featuring integrated socio-metabolic and political-economic dimensions. In socio-metabolic terms, material stocks-buildings, infrastructures, and machines, for example-are key components of provisioning systems and transform flows of energy and materials into goods and services. In political-economic terms, provisioning systems are formed by actors, institutions, and capital. We loosely identify and closely analyze, from socio-metabolic and political-economic perspectives, five phases along which provisioning systems are shaped and in which specific opportunities for interventions exist. Relying mainly on examples from the fossil-fueled electricity system, we argue that an integrated conceptualization of provisioning systems can advance understanding of these systems in two essential ways: by (1) facilitating a more encompassing perspective on current forms of provisioning as relying on capitalist regulation and on material stocks and flows and by (2) embedding provisioning systems within their historical context, making it possible to conceive of more sustainable and just forms of provisioning under (radically) altered conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".