In Ice and Skin: Inuit Kakiniit Birth, Death, and Revival in a Modern Post-Colonial and Politicized Arctic
Bibliographic record
Abstract
This paper delves into the profound history of traditional Inuit tattooing practices known as kakiniit against the backdrop of a post-colonial and highly politicized Arctic landscape. The story of the birth, death, and revival of kakiniit is amidst many traces of Indigenous resilience and transformation following rapid socio-cultural changes within communities during assimilatory efforts. Highlighting the narrative perspectives surrounding the birth of kakiniit, this paper serves the history of the artistic storytelling model and form of cultural expression through Inuit cosmologies and ontologies and revisits sites of its cultural preservation and revitalization, interrogating lingering assimilatory perspectives within the Arctic wherein colonial impositions intersect with Indigenous agency. Through the study of ethnographic narratives across age groups and geographies and engagement with contemporary resurgence efforts, this essay illuminates the deep-rooted complexity and dynamic adaptation of kakiniit throughout the ages, navigating its creation, temporary expulsion from Inuit culture and its revival and repurposing as a widely used historical recognition and cultural reclamation practice across Indigenous cultures in the Arctic as an adaptive expression of cultural continuity and resistance in the face of ongoing colonialist ideals.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.021 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| 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".