Bibliographic record
Abstract
Colonial regimes of sounds used to represent Inuit—what one might shorthand as “the Sound of Eskimo,” an Arctic complement to Deloria’s “Sound of Indian”—can be traced back to cue sheets, scores, and soundtracks that accompanied Robert Flaherty’s Nanook of the North (1922). A lack of musical and cultural specificity granted to Arctic Indigenous Peoples represented in film over the long twentieth century is due to misplaced assumptions about circumpolar lands, waters, and lifeways as monolithic. Until the 1970s, ethnographic records about Inuit lifeways and music-making also lacked radical and relational approaches to research that acknowledged the particularities among and between Inuit communities and performance practices across the Arctic. This chapter traces important shifts over the past century, from non-Inuit ethnologists to Inuit filmmakers, and offers in-depth analyses of soundscapes and soundtracks from Iñupiaq filmmaker Andrew Okpeaha MacLean’s award-winning feature film On the Ice (2010). The author emphasizes three on-screen musical performances—Iñupiaq drumsong, “Eskimo flow” hip hop, and a singspiration, or Presbyterian hymn singing—that archive dense histories of colonization and resurgence in Utqiaġvik.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.002 |
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".