Decolonising the NDIS: a third space to account for First Nations' values
Bibliographic record
Abstract
Purpose This paper aims to investigate how embedding accounting techniques of cost and budgeting within the Australian National Disability Insurance Scheme (NDIS) potentially perpetuates colonial practices for Australian First Nations people living in remote areas. Further, the paper aims to explore how accounting might help to integrate the unique modes of accountability First Nations people have over disability care into the NDIS funding system. Ultimately, the aim is to discern whether accounting practices can be mobilised as a means to decolonising the NDIS framework. Design/methodology/approach This study uses a qualitative methodology to analyse public hearings from the Australian Disability Royal Commission. Drawing on Bhabha's (1994) concept of the “third space”, this study investigates how accounting techniques can be used to potentially decolonise the NDIS. This study also borrows Bhabha's (1994) concept of the third space to explore the potential for decolonising the NDIS through accounting techniques. Findings Findings show that the accounting techniques pertaining to funding and costs embedded within the NDIS contribute to displacing and disconnecting First Nations people from their cultural practices and ways of life. Further, the analysis reveals that the NDIS funding system could help to decolonise the NDIS space if it were modified to incorporate First Nations' perspectives on accountability for disability care. Originality/value The case of the NDIS exposes glimpses of colonisation in contemporary Australia, where Western institutional and economic systems dominate over the structure and authority of the practice. In this paper, this study demonstrates that the accounting system used by the NDIS plays a role in marginalising First Nations people. However, accounting, as a technology of negotiation, could also be mobilised to enhance accountability for disability care outcomes and pave the way for decolonising public policies.
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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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.039 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".