If this is your land, where is your camera?: Atanarjuat, The Journals of Knud Rasmussen and post-cinematic adaptation
Bibliographic record
Abstract
Abstract As unique examples of the contemporary, transnational art film, Zacharias Kunuk and Norman Cohn’s Atanarjuat (2001) and The Journals of Knud Rasmussen (2006) are stylistically distinct, their formal differences traceable to each film’s provenance as an adaptation of a specific type: Atanarjuat adapts an Inuit myth; The Journals of Knud Rasmussen sections of the ethnographer’s actual journals. At the same time, as remediations of radically different media forms, these films can be read according to the categories outlined by Jan Assmann, respectively, embodying ‘the normative and formative values of a community, its “truth”’, answering the questions ‘Who are we?’ and ‘What shall we do?’. These films also correspond to Astrid Erll’s categories of memory-productive and memory-reflexive film, respectively, reflecting formally and thematically upon Inuit cultural memory in the digital era. This article explores the myriad implications for cultural memory of this marriage of cutting-edge digital video technology with ancient themes and folkways, in effect a pre-literate ‘oral’ culture translated seemingly wholesale to the screen. I consider these Inuit films in terms of the question of cultural memory as it becomes trans-cultural, and national cinema as it becomes trans-national, while the local and ‘indigenous’ find representation at a level of global legibility.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".