Bibliographic record
Abstract
The history and geography of intellectual neglect of Marxism are the history and geography of Marxism itself. Scholars of different political persuasions and from different regions of the world, including some ‘Marxists’, have pointed to its various deficiencies ever since its origin. But is Marxism really as bad as it is made out to be? In this short article, I argue that it absolutely is not. I discuss my view of Marxism, including Marxist geography. The latter examines economy, politics, culture and nature/body from the vantage-point of space, place, scale and human transformation of nature. I also discuss what difference Marxism has made to my own agenda of abstract and concrete research. For me, Marxism fundamentally comprises ideas of Marx and Engels, and revolutionary Marxist socialists of the 20th century (Lenin, Luxemburg and Trotsky), and those who have critically developed their thinking. I discuss four major areas of Marxism: philosophy (dialectical and materialist views of society and nature), social theory, or historical materialism, (geographical) political economy, and theory of communist practice. Marxism treats class, including in its capitalist form, as the causally most important social relation which explains how human beings live their lives. Class relations, and capitalism, structure gender and racial oppression which in turn influence class relations at a concrete level, and which are behind the geographical organization of society. The main goal of Marxism is not to produce ideas for the sake of ideas. It is rather to arm the exploited masses with adequate ideas that describe, explain and critique the world from their standpoint, so they can engage in the fight to produce an alternative social-spatial arrangement, i.e. a democratic and classless society which is ecologically healthier and which avoids geographically uneven development intra-nationally and internationally.
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 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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.061 |
| Scholarly communication | 0.028 | 0.056 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".