‘Blond Beasts of Prey’: A Nietzschean interpretation of the language of Britain's colonisation of New Zealand
Bibliographic record
Abstract
This article explores the efficacy of applying Friedrich Nietzsche's hypothetical reconstruction of the emergence of human morality, to examples of the language used by agents of the British colonisation of New Zealand in the nineteenth century, with a particular focus on notions of cultural and racial superiority/inferiority. The particular nexus of psychology and philosophy that Nietzsche formulated provides a useful ontological framework for examining the phenomenon of colonisation, especially its often explicitly racial orientation. Nietzsche's architecture of the history of morality, with its constituent elements of race, mastery, civilisation, savagery, morality, imperial expansion, and pan-Europeanism, is evident in much of the language used by various agents of Britain's colonisation of New Zealand in the nineteenth century. The analogies are not always exact, and the connections are correlative rather than causative (necessarily so, on the basis that Neitzsche's reconstruction of the emergence of human morality is retrospectively applied in this article), but the particular nexus of psychology and philosophy that Nietzsche formulated does provide a useful ontological framework for examining the phenomenon of colonisation, especially its often explicitly racial orientation. Nietzsche's theories in this area also resonate with the notion of settler colonialism, in which an expanding dominant population spreads out into new territories, and then encodes and reproduces the unequal relationships that it has used to coerce other populations during previous phases of its expansion. The conclusion reached is that Nietzsche's architecture of the history of morality, despite being largely conjectural, can serve as a theoretical model that assists in interpreting and contextualising some of the language that accompanied Britain's colonisation of New Zealand in ways not afforded by other theoretical approaches.
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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 | 0.005 | 0.022 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".