Bibliographic record
Abstract
Introduction Joanna Hearne (bio) Māori writer, director, and performer Taika Waititi's land acknowledgment at the 2020 Academy Awards ceremony might be the biggest Indigenous moment at the Oscars since 1973, when Marlon Brando declined his award and Sacheen Littlefeather took the microphone in his place to make a statement supporting the American Indian Movement's occupation of Wounded Knee. Waititi's acknowledgment of the Tongva, Tataviam, and Chumash as "the first peoples of this land on which the motion pictures community lives and works" ricocheted across the internet.1 Indigenous responses ranged from Nick Martin's remarks about the "dissonance" of land acknowledgments in the face of public apathy on Indigenous issues to Heperi Mita's deeply appreciative contextualization of Waititi's achievements within a Māori "filmmaking whakapapa."2 Whakapapa is often defined as "geneaology," the ordering of generations and the relations among their stories, although the term also entails broader concepts fundamental to Māori worldviews and epistemologies; Mita invokes it here to foreground Indigenous relationality across multiple generations of filmmakers. Indeed, this moment—Waititi's win and his speech—has multiple genealogies, some obvious and others more hidden, because Indigenous participation in film and media production has occupied contradictory positions of invisibility and hypervisibility for a very long time. In the face of long-term erasure from the screen—with Indigenous participation both limited and often [End Page 152] unacknowledged—"our presence is our weapon," as Michi Saagiig Nishnaabeg poet and scholar Leanne Betasamosake Simpson writes.3 While Simpson uses "presence" broadly to indicate Indigenous survival of "centuries of attack," I cite her phrasing here to point more specifically to the resilience and endurance of historical and ongoing communities of Indigenous performers and filmmakers. Recognizing this presence and power re-centers Indigenous participation in North American film and media; it draws our attention to offscreen production networks and infrastructures, interventions in regimes of redfacing, and the leveraging of hard-won screen visibility to support political resistance movements such as #MMIW (missing and murdered Indigenous women) and #NoDAPL (No to the Dakota Access Pipeline). Building on Dakota scholar Philip Deloria's work, we find "Indians in unexpected places" in film and media.4 Faced with screen images of "vanishing Indians," we see evidence of Indigenous presence, from early cinema to the Hollywood studio system to independent media arts to contemporary television and digital media. Through historical recovery and print, digital, and interview research, we "re-credit" the work of Indigenous performers, filmmakers, and digital media artists, making visible their pathways across professional and political networks.5 In recognizing and documenting these artists' Indigenizing strategies, we Indigenize the historical record and expand the field to include new readerships. When we Indigenize film and media history, we are able to ask new questions: What were the stories of the uncredited extras seen in film backgrounds or alongside white stars performing in redface? Who were they and what were the conditions of their participation? What behind-the-scenes negotiations took place between directors and producers and the Indigenous consultants they hired for productions? When Indigenous performers were embedded in productions or exhibitions, how did they use the limited power and visibility they had within the system—or, through publicity, outside of it—to further agendas related to labor, representation, or community concerns? How did Indigenous filmmakers, performers, audiences, and other participants form their own professional or fan communities around shared concerns such as casting, training, and activist interventions in systems such as Canadian media arts organizations or social media platforms? How did they translate concerns with political sovereignty to aesthetic choices for the screen? The scholars in this dossier address these questions by centering Indigenous media genealogies—and more broadly, Indigenous ethics of care and relationality—in both content and methodology. This In Focus analyzes Indigenous performance networks as forms of offscreen community building and activism in relation to screen media. Indigenous participation in mainstream and independent film industries has been the subject of significant historical recovery, even as scholars also address the emergent forms of Indigenous media activism arising with new digital [End Page 153] platforms. The essays collected here investigate Indigenous offscreen practices either independently or alongside...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".