Charles Darwin: towards a bio-religious and colonial genealogy of evolutionary being
Bibliographic record
Abstract
While studies have examined Charles Darwin's wide social and political impact, they have not adequately centred the combined influence of colonial systems of human differentiation and religion within them. To address this, I draw from Sylvia Wynter's critique concerning how religious and colonial discourses contribute to the shifting development of Man within the Western tradition. Specifically, I explore how Darwin focused his evolutionary gaze towards one of the unique foundations of what it meant to be human in his time: religion. Tracing the entangled religious and colonial filiations of Darwin's thought, I show that he established an evolutionary link between human and non-human animals by proposing both Indigenous peoples and dogs held superstitious beliefs. To illustrate this, I show that Darwin transposed Victorian anthropological conceptions of religion - as a quantifiable object of knowledge corresponding to the intellect and associated with phrenology, dream theory and the apparitional soul - into a bio-religious conception of evolution. Furthermore, I argue that Darwin's bio-evolutionism assumes Christianity is most closely associated with abstract reason. Finally, analyzing the role of race in Darwin's thought, I suggest that theology is not what was before modern scientific bio-evolutionary conceptions of race, but at its very core.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.030 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".