Environmental Failure, Success and Sustainable Development: The Hauraki Plains Wetlands Through Four Generations of New Zealanders
Bibliographic record
Abstract
Abstract From 1875 to 1920 the floodplains of the Hauraki Plains, the largest wetland complex in New Zealand, were almost entirely transformed through logging of kahikatea, diking and canalising of rivers, and drainage of the land. One of the world's most biologically diverse landscapes, millennia in the making, and sustainably exploited for centuries by Maori, was transformed by Pakeha colonists (White newcomers) into a landscape dominated by grass. This environmental transformation is interpreted as a result of culture: a colonial people whose culture blinded them to other ways of interacting with wetlands. Taking a long-term approach following one family of Pakeha through four generations of interaction with the Hauraki Plains wetlands, this study argues that the environmental transformation that happened there was less a question of culture than of a specific time and place (context of civilisation). As contexts of civilisation changed, and as later generation Pakeha became New Zealand-born, their sense of place, and especially the understanding of their place within the environment, changed. Ironically, restoration of the wetlands and the future of sustainable development in places like the Hauraki Plains are dependent on the past, on people better understanding the environmental failures and successes of their ancestors, and that no people are axiomatically predisposed by culture to be environmental destructors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".