First Nations' pop-cultural heroes: Indigenous communication practices in the age of mass media
Bibliographic record
Abstract
This doctoral thesis examines innovative forms of media making in Australia with a focus on a new generation of writers and artists working in popular media formats that are not getting sufficient attention in scholarly literature. This thesis situates two in-depth case studies of Australian Aboriginal media franchises, Jordan Gould and Richard Pritchard's Wylah the Koorie Warrior (2022-) and Jonathon Saunders' Zero Point (2016-), within the dual histories of First Nations media production and mainstream appropriations of First Nations identities within popular culture. As I study the criticism of two Disney films, Pocahontas (1995) and Moana (2016), I find that tackling problems of representation with seemingly effective strategies of cultural research and consultations with cultural experts is not, in fact, a straightforward and infallible solution. By investigating how Gould, Pritchard, and Saunders engage with pop-cultural production and what messages they intend to communicate to their cross-sectional audience, I unpack some of the complexity of Indigenous engagement with contemporary mass media in general, and Indigenous identity representation specifically. These franchises reveal insights into the complex, multilayered, and politicised space of Australian Indigenous mass media. By analysing forms, storylines, readerships, business models, political contexts, positionality of authors, and historical trajectories, I find that this field represents a novel development in Australia and that Indigenous media creators negotiate utilisation of media technologies to articulate their own relatively autonomous concerns. The Indigenous identity of the media creators I worked with does have a profound impact, that is both enabling and limiting, on their production process, funding, career and marketing opportunities, and relationship with their audience. I find that the meaning and place of Indigenous cultural identity in the current socio-political state of Australia is the subject of intense negotiations linked to political, cultural, and social divides within society. In the end, I explain that viewing Indigenous communication practices as relatively autonomous components of Indigenous cultural systems helps in viewing Indigenous mass media use without leaning into the essentialist rhetoric of Indigenous cultural authenticity or social amalgamation into the wider Western society.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.022 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".