Revisiting the ‘Darwin–Marx correspondence’: Multiple discovery and the rhetoric of priority
Bibliographic record
Abstract
Between the 1930s and the mid 1970s, it was commonly believed that in 1880 Karl Marx had proposed to dedicate to Charles Darwin a volume or translation of Capital but that Darwin had refused. The detail was often interpreted by scholars as having larger significance for the question of the relationship between Darwinian evolutionary biology and Marxist political economy. In 1973–4, two scholars working independently—Lewis Feuer, professor of sociology at Toronto, and Margaret Fay, a graduate student at Berkeley—determined simultaneously that the traditional story of the proposed dedication was untrue, being based on a long-standing misinterpretation of the relevant correspondence. Between the two, and among several other scholars who became their respective allies, there developed a contest of authority and priority over the discovery. From 1975 to 1982, the controversy generated a considerable volume of spilled ink in both scholarly and popular publications. Drawing on previously unexamined archival resources, this article revisits the ‘case’ of the so-called ‘Darwin–Marx correspondence’ as an instance of the phenomenon of ‘multiple discovery’. A familiar occurrence in the natural sciences, multiple discovery is rarer in the humanities and social sciences. The present case of a priority dispute in the history of ideas followed patterns familiar from such disputes in the natural sciences, while also diverging from them in ways that shed light on the significance of disciplinary norms and research infrastructures.
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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 | 0.034 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.013 | 0.119 |
| Scholarly communication | 0.019 | 0.036 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".