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Record W3152917952

Marx, Capital, and the Madness of Economic Reason; The Ways of the World

2021· article· en· W3152917952 on OpenAlexvenueno aff
Jeff Noonan

Bibliographic record

VenueAlternate routes · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsnot available
Fundersnot available
KeywordsCapital (architecture)Neoclassical economicsCapitalismEconomicsSociologyPolitical scienceArtPoliticsVisual artsLaw
DOInot available

Abstract

fetched live from OpenAlex

David Harvey is one of the world's best known radical intellectuals.He has achieved this status despite the fact that his disciplinegeographyis one which, like my own (philosophy) everyone has heard of but would be hard pressed to define if asked.If I were asked, I would risk defining geography as the study of spatial relationships.Since there is no "space" apart from things and people standing in spatial relationships, geography and philosophy have one more thing in common: anything at all can become an object of geographical or philosophical study.Harvey first came to prominence within geography circles as a student of the formation of urban spaces.His studies of ghetto formation in Baltimore made him realize that what happens in cities cannot be understood apart from what happens within the economic system generally.His interest in particular places thus led him to the study of global political economic dynamics at a time when cities were becoming central to new capitalist growth dynamics and 'globalization' was on everyone's mind.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0050.059
Scholarly communication0.0150.014
Open science0.0010.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.266
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations0
Published2021
Admission routes1
Has abstractno

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