Mixed-Race Kanak in “a World Cut in Two”: Contemporary Experiences in Kanaky/New Caledonia
Bibliographic record
Abstract
This article interrogates how the profound history of spatial segregation across colonial, racial, and cultural lines appears in contemporary narratives of mixed-race people in Kanaky/New Caledonia (K/NC). By tracing the moments that specific spaces, such as “the city” and “the tribe,” are mentioned in these narratives, the article shows how the colonial divide structures selves, relations, spaces, and society and manifests itself in discussions with self-identified métis/ses Kanak-White people, especially in the context of the formal decolonization process K/NC is going through. The research draws primarily on interviews with self-identified métis/ses Kanak-White people that took place a few months before the 2018 referendum for independence. The primary question this article seeks to answer is: how does French colonialism spatially determine the lives of métis/ses in K/NC? For this purpose, it analyzes how métis/ses Kanak-White people navigate the variety of spaces they inhabit through experiences of everyday racism and explores how spatial polarization appears in their stories, particularly given the significance of the land for Kanak identity. Notably, the article shows how colonial rhetoric transpires in these different spaces by way of regulating whether the métis/se body belongs within a particular space.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.016 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".