CEREMONY AND STORYWORK: DECOLONIZING STRATEGIES IN CONTEMPORARY INDIGENOUS DOCUMENTARY FILM
Bibliographic record
Abstract
This dissertation centers on multiple Indigenous-directed documentary and experimental films directed by an emerging class of Indigenous storyworkers who are making space on the cinematic screen to increase society’s consciousness of Indigenous peoples and their stories. I focus on films produced between 2015-2022 from six Indigenous directors representing diverse Indigenous communities from within Canada and the United States: Alethea Arnaquq-Baril (Inuit), Christopher Auchter (Haida), Sarain Fox (Ojibwe), Sky Hopinka (Ho-chunk), Tasha Hubbard (Plains Cree), and Ciara Lacy (Native Hawai’ian). These Indigenous documentarians have been generating a dynamic wave of cultural productions that contribute to Indigenous knowledge production, enact and represent narrative sovereignty, strengthen Fourth Cinema’s presence within the broader filmmaking world, and counter or question perceived universal truths stemming from Eurocentric hegemonic thought. The collection of films contains overlapping themes of culture, family, community (an expanded notion of community) as well as demonstrate a reverence for Indigenous language, Indigenous voices, and ancestral memory. To complete this study, I draw upon the guiding principles of Indigenous storywork (Archibald, 2008) and pair these principles with the practice of neurodecolonization (Yellow Bird, 2012, 2016, 2019) in order to synergistically prepare for and engage with the nine selected Indigenous-directed films. I call this combined approach a decolonizing cinematic engagement practice. I also reflect and remark on what it means to adopt a decolonizing cinematic engagement practice and offer it as a humble gift for Indigenous students. I assert that the pairing of Indigenous methodology with Indigenous method expands the breadth and depth of intellectual pathways and generates novel possibilities for students of documentary film as well as students of Indigenous studies. In alignment with these approaches, I present this dissertation through the overarching metaphor of the contemporary Indigenous powwow in order to provide Indigenous readers with culturally-specific directional signposts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.008 |
| 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".