Storing value: The infrastructural ecologies of commodity storage
Bibliographic record
Abstract
As Marx pointed out in the second volume of Capital, storage is a critical moment in the circulation of capital. Yet, despite the resurgent interest in the political economy of circulation, logistics, and infrastructures, commodity storage remains under-examined in critical human geography. This paper examines the “hidden abode” of storage by tracing attempts to control moisture and realize value in two different commodity chains: Newfoundland saltfish and American grain in the late-19th- and 20th centuries. Storing preserved codfish and grain presented different biophysical obstacles for firms, but both required interventions to discipline moisture to preserve and realize the value embodied in the commodities. Through our empirical work, we frame storage sites as infrastructural ecologies: complex, more-than-human assemblages that both constrain and enable the realization of value embodied in lively commodities. This paper contributes to debates on circulation, logistics, and infrastructures by highlighting historical geographies of storage as a novel vantage point from which to analyze the frictions and flows of value under capitalist social relations. By grounding logistics in a value-theoretical framework, this paper also contributes to recent debates regarding the value (and valuation) of nature in political economy, by highlighting the role of storage and realization in the nature–value nexus.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.030 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".