Compensatory justice and accountability for First Nations peoples: the Timber Creek case
Bibliographic record
Abstract
Purpose This paper examines the state’s accountability to its citizens, in particular the First Peoples of settler colonial nations such as Australia, and how these responsibilities may be enacted via a process of compensatory justice in Native Title claims. We focus on the landmark Timber Creek ruling and the impacts of racialized preconceptions on the accountability outcomes of the case. Design/methodology/approach This study draws on critical race theory to reveal embedded racialised perspectives that perpetuate exclusion and discriminatory outcomes. Court documents including hearing transcripts, case judgements, witness statements, appellant and respondent submissions, expert reports and responses from First Nations leaders, form the basis of our analysis. Findings The case highlights how the compensation awarded to Native Title holders was based on racialised assumptions that prioritised neoliberal values, commercial activities and reaching a “socially acceptable” judgement over valuing Aboriginal uses of land. A critical analysis of court documents reveals the pervasiveness of presumed “objectivity” in the use of accounting tools to calculate economic value and the accountability implications of a process based on litigation, not negotiation. These findings reveal the hiding places offered by calculative practices that equate neoliberal priorities with accountability and reaffirm the importance of alternative accountings to resist inequitable distributive outcomes. Originality/value Novel insights, drawing on First Nations peoples’ connections to land and their perspectives on accountability and justice, are offered in this study. Our analysis of Native Title holders’ submissions to the courts alongside historical and anthropological sources leads to the conclusion that compensation decisions regarding Native Title land must be approached from the perspective of Aboriginal landowners if accountable outcomes are to be achieved.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| 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".