Bibliographic record
Abstract
The need to protect threatened species and facilitate their recovery to viable population levels enjoys widespread international support, but it is the domestic legal rules of individual nations that will implement international calls for protection and recovery. New Zealand purports to protect threatened species primarily with the Wildlife Act 1953, a statute whose purpose is more concerned with wildlife management than implementing a legal framework to protect threatened species. The consensus is that the Wildlife Act 1953 and other applicable legislation such as the Resource Management Act 1991 is not up to the task of protection and recovery of threatened species in New Zealand. In this article we explore how dedicated threatened species legislation in New Zealand might improve on the existing legal framework, and in particular with respect to the designation and planning on threatened species, recovery programmes and habitat protection. For an illustration of how these components may contribute to the threatened species problem we look to Canada as a nation which enacted dedicated threatened species legislation in 2002. The story thus far in Canada suggests legal rules are not a panacea for species decline, but nonetheless dedicated legislation can offer substantial benefits such as transparency and a systematic approach to species planning, better integration with resource development, and a measure of accountability in law to hold public officials to their promises on threatened species protection.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".