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Record W4399236465 · doi:10.1177/0308518x241254664

Does capitalism drive towards the commodification of everything?

2024· article· en· W4399236465 on OpenAlexaff
Derek Hall

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsWilfrid Laurier UniversityBalsillie School of International Affairs
Fundersnot available
KeywordsCommodificationCapitalismBusinessMarket economyNeoclassical economicsEconomicsPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

The claim that capitalism drives to commodify everything is widely made in late-20th century and early-21st century critical political economy and plays a central role in prominent theoretical frameworks and texts. The argument is, however, rarely articulated in any detail, and proponents do not explain why capitalism would drive to commodify not just very many things but everything. In this paper I carry out the first systematic review and critique of works making the claim. I show that the literature fails to define ‘everything’ and ‘the commodification of everything’ and identify significant weaknesses in the six implicit argumentative strategies these works employ. I also show that positions that might appear to reject the claim do not get traction on it. In the second section I reconstruct the argument by defining terms, positing six commodifying mechanisms that should emerge from capitalism’s core features, and searching for ‘things’ the literature has ignored. The search draws especially on historical research into surprising examples of commodified violence, governance, authority and monopoly. My analysis both greatly expands the literature’s theoretical and empirical scope and argues that capitalism generates decommodifying drives with respect to certain key ‘things’. Capitalism does not drive towards ‘the commodification of everything’ under any non-trivial definition of the latter term.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.247
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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