Rewilding the world: dispatches from the conservation revolution
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
Scientists worldwide are warning of the looming extinction of thousands of species, from tigers and polar bears to rare flowers, birds, and insects. If the destruction continues, a third of all plants and animals could disappear by 2050 - and with them earth's life-support ecosystems that provide our food, water, medicine, and natural defenses against climate change. Now Caroline Fraser offers the first definitive account of a visionary campaign to confront this crisis: rewilding. Breathtaking in scope and ambition, aims to save species by restoring habitats, reviving migration corridors, and brokering peace between people and predators. Traveling with wildlife biologists and conservationists, Fraser reports on the vast projects that are turning Europe's former Iron Curtain into a greenbelt, creating trans-frontier Peace Parks to renew elephant routes throughout Africa, and linking protected areas from the Yukon to Mexico and beyond. An inspiring story of scientific discovery and grassroots action, Rewilding The World offers hope for a richer, wilder future.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it