Bibliographic record
Abstract
This article outlines the fraudulent practices of settler traders and land agents who employed alcohol to facilitate the alienation of Māori lands, highlighting the close relationship between Māori, liquor and land loss in 19th century New Zealand. Traders and agents developed a range of strategies, forged in Britain, tempered by colonial experience and wielded with deft precision in New Zealand to defraud Māori of their lands. Government efforts to pre-empt and prevent the worst excesses of settler crime proved ineffectual, self-defeating, paternalistic and ultimately unenforceable. Māori came to regard settler practices, the successive failure of legislation to alleviate the problem, and state connections with the liquor industry to be part of a thinly veiled conspiracy to destabilize their communities and alienate their lands. While this conclusion is highly problematic, it is likely that traders and agents had witnessed or were aware of similar practices in the settler colonies of Australia, Canada and North America, and made good use of them in New Zealand to access Māori lands.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".