Bibliographic record
Abstract
At its Canadian premier, Dominic Gagnon's Of the North (2015) launched a passionate debate regarding the ethics of image appropriation and digital filmmaking about Indigenous communities. Of the North follows Gagnon's “natively” digital method, which involves the sampling and montage of public domain images and sounds posted by internauts with the stated intent of documenting how people represent themselves online. In a controversy that crystallized around questions of “digital sovereignty,” Inuit critics decried the recontextualization of personal video posts by a film, they argued, that did not promote an Inuit view of Inuit experience. This article addresses the ways in which Gagnon's digital method collapsed cultural contexts, bringing to light divergent cultural and generational expectations regarding digital presence and sovereignty. An analysis of the film's heated reception and new digital works by young Indigenous filmmakers suggests an intercultural ethics for visual ethnographies.
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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 | 0.013 | 0.035 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".