Indigenising masculinities: Relational renewal in settler colonial Australia
Bibliographic record
Abstract
This article argues that Indigenising masculinities is both a practice of cultural renewal and a necessary response to the crisis of manhood in settler-colonial Australia. Drawing on Indigenous standpoint theory, settler colonial studies, and critical masculinity scholarship, it shows how dominant gender norms, rooted in whiteness, hierarchy, and individualism, marginalise Indigenous men while also constraining settler men. We introduce three new conceptual tools: a masculinities analytical continuum, which illustrates the shifting, relational spectrum between Indigenous and settler-colonial forms of manliness; ERASE, which maps the exclusionary logics of settler masculinities; and GROW, a relational framework grounded in kinship, law/lore, care, and cultural responsibility. Indigenous masculinities are defined here as dynamic, diverse, and sustained through storytelling, ceremony, and obligations to kin and Country. We distinguish Indigenisation from decolonisation, emphasising that both must occur together: the former led by Indigenous peoples, the latter the responsibility of settlers. Although centred in Australia, the conceptual tools developed here have broader relevance for contexts such as Canada, Aotearoa (New Zealand), the United States, Hawai'i, and beyond, where colonial and Indigenous gender orders intersect. Indigenised masculinities offer not only a critique of colonial power but also a generative foundation for more ethical, caring, and sustainable ways of being for all men and male-identifying people.
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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 | 0.004 | 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 | 0.022 | 0.038 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".