Negotiating claims: comparing state responses to indigenous land claims in Australia, Canada, and New Zealand
Bibliographic record
Abstract
My research builds on existing literature on Aboriginal-State relations through its comparative examination of State responses to Aboriginal land claims . The histories of Aboriginal collective action show that Aboriginal peoples have consistently petitioned governments to address their claims; what varies is the response of the State to those claims and the effectiveness of those responses. I am interested in exploring the conditions under which governments create a negotiating space through which Aboriginal land claims are collected, examined, negotiated, and settled. Why Aboriginal peoples would want to engage the State to move on outstanding claims is fairly clear; less clear is why and under what conditions governments choose to engage with Aboriginal peoples qua Aboriginal peoples in a negotiated settlement process. The central question I ask is thus: why do governments choose to bargain with Aboriginal peoples to settle outstanding land claims? The significance of this question is simple. The ownership of lands and the power of the State to determine rights to the use and enjoyment of lands is central to the relationship of power between the State and Aboriginal peoples. To examine the conditions under which governments choose to respond to Aboriginal claims to their ownership and use of land is critical to examining change in Aboriginal-State relations. It speaks to central questions in political science: the relations between State and society, particularly changing relations between the State and a historically marginalized sector of society. This paper draws on approximately 50 interviews I have conducted since September 2001 in Canada, New Zealand, and Australia. I have spoken primarily with government policy makers, but I have also spoken with Aboriginal legal and political representatives, Aboriginal claimants, academics, and industry representatives. My approach is to focus on how the various players in the negotiations process view their own strategic objectives, the strategies and objectives of the other players, and the role of uncertainty—both judicial and economic -- in land claims negotiations. In this paper I focus on three issues and how they impact the modern context of land claims negotiations. These are: 1) the impact of the historical practice of signing treaties between Aboriginal peoples and the Crown; 2) the role of litigation in affecting State behaviour, and 3) the impact of federalism, or the constitutional division of State power between two levels of government over the public policy space. These three issues do not exhaust all that is interesting or at play in these negotiations, but are in my opinion critical in understanding who is sitting around the negotiation table, why they are sitting there, why they continue to sit there, and whether, at the end of the long day, a settlement is reached.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".