INDIGENOUS DISCURSIVE ACTIVISM AGAINST EPISTEMIC OPPRESSION. TRANSMEDIA (HI)STORYTELLING AS A THEORY-PRACTICE FRAMEWORK FOR RADICAL RESURGENCE
Bibliographic record
Abstract
This proposal starts from the assumption that Indigenous transmedia storytelling offers both a context and an analytical opportunity for reframing theories and practices of decoloniality. From dismantling settler-colonial narrative regimes to problematising neocolonial scopic orders through native transmedia activism, this contribution endeavours to challenge regime-made socio-cultural tropes for the purposes of a re-politicisation of Michi Saagiig Nishnaabeg epistemologies. Indigenous literary production more broadly is deeply informed by Native Americans’ holistic engagement with their intellectual, political, artistic and spiritual life (Simpson 2017), reflecting the way in which the ontological foundations of their intelligence systems are embedded in a multi-layered process of knowledge production. Within the context of Nishnaabeg intellectualism, the definition of radical resurgence – understood as a comprehensive change rather than a violent act (ibidem) – may seem redundant. However, this redundancy is justified, as Western thought compartmentalises the cultural and political spheres as mutually exclusive aspects of public life. For this reason, the term cultural (resurgence) fails as a consistent modifier, as it undermines Indigenous claims of dispossession and erasure as political issues. Therefore, drawing on the theoretical framework of decoloniality (Mignolo 2009; Geniusz 2009; Smith 2012; Tuck & Yang 2012), this contribution aims to investigate transmedia Indigenous narratives as conduits for local-cultural knowledge production and global visibility through epistemic recognition. It does so by examining the works of Nishnaabeg scholar and artist from Canada Leanne Betasamosake Simpson: the genre-blending novel Noopiming: The Cure for White Ladies (2020), which significantly influenced her digital album Noopiming Sessions, and was at the same time informed by her video-poem How to Steal a Canoe (2016). The selected case studies represent compelling manifestations of how Indigenous content is inherently remixable, exemplifying non-dichotomous approaches to knowledge-building processes, and embodying Indigenous “grounded normativity” – that is, how Native Americans’ land-based knowledge shapes their reciprocal and non-exploitative commitment to the world (Coulthard 2014). Thus, serving as a ‘cultural activator’ (Jenkins 2008, p. 101), Indigenous – and specifically Anishinaabe – transmedia storytelling fosters self-representational narratives, positioning them as practices of active citizenship oriented toward sociocultural, political, and eco-aesthetic resurgence.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.057 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".