Rethinking protected area categories and the new paradigm
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The World Conservation Union (IUCN) plays a global leadership role in defining different types of protected areas, and influencing how protected area systems develop and are managed. Following the 1992 World Parks Congress, a new system of categorizing protected areas was developed. New categories were introduced, including categories that allowed resource extraction. Since that time there has been rapid growth in the global numbers and size of protected areas, with most growth being shown in the new categories. Further-more, the IUCN has heralded a ‘new paradigm’ of protected areas, which became the main focus of the 2003 World Parks Congress. The paradigm focuses on benefits to local people to alleviate poverty, re-engineering protected areas professionals, and an emphasis on the interaction between humans and nature through a focus on the new IUCN protected area categories.The purpose of this paper is to examine critically the implications of the new categories and paradigm shift in light of the main purpose of protected areas, to protect wild biodiversity. Wild biodiversity will not be well served by adoption of this new paradigm, which will devalue conservation biology, undermine the creation of more strictly protected reserves, inflate the amount of area in reserves and place people at the centre of the protected area agenda at the expense of wild biodiversity. Only IUCN categories I–IV should be recognized as protected areas. The new categories, namely culturally modified landscapes (V) and managed resource areas (VI), should be reclassified as sustainable development areas. To do so would better serve both the protection of wild biodiversity and those seeking to meet human needs on humanized landscapes where sustainable development is practised.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it