Circular Economy and First Nations Communities in Australia: A Policy Perspective
Bibliographic record
Abstract
ABSTRACT Sustainable material consumption and waste management have become urgent priorities for many nations globally. The circular economy has emerged as a viable response to these challenges, which offers a systems‐based approach with long‐term resilience outcomes. Its successful implementation, however, relies on the collective efforts of multiple stakeholders, including communities. In Australia, First Nations communities possess unique knowledge systems and practices, shaped by deep connections to Country and sustained over millennia, that align closely with circular economy principles. Recognising and valuing these contributions within circular economy policies is essential, not only as a matter of justice and respect, but also to ensure equitable access to the benefits of relevant initiatives. Despite their significance, no prior study has systematically examined how First Nations communities are represented or acknowledged in Australian waste and circular economy policy frameworks. This research addresses this gap by analysing the relevant Australian policies to further understand the extent and nature of First Nations communities' inclusion across government policies, guidelines and action plans. Using the PESTEL‐CA framework, this study also reviews the relevant literature to identify factors that drive or hinder their engagement with circular economy initiatives. Based on the insights gained through policy analysis and literature review, a stakeholder‐oriented guiding framework was developed to support more inclusive and culturally responsive policy and practice. The framework clarifies the roles and interactions among key actors and serves as a practical tool to guide future reforms. These findings have broader implications for embedding the social dimension into Australia's transition to a circular economy.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 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".