Moving from Ecological Conservation to Restoration: An Example from Central Taiwan, Asia
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 concept of “natural conservation” has been evolving since the beginning of the first efforts to preserve the natural landscape. The creation of the first national parks in the 19th century was originated by the belief that landscapes of exceptional beauty should be preserved from human influence and maintained in their current state for the enjoyment of future generations (Runte, 1997). During the first years of the establishment of national parks around the world, defining these “exceptional landscapes” was usually based on the static beauty of the area: majestic mountains, glaciers, old forests, gorges, canyons, waterfalls, etc. The protection in these areas was basically achieved through the prevention of creating human structures in the sites, reducing and controlling human activity and, in practice, maintaining the areas as they look at the time when they were declared as protected. Therefore, this protection was not based on ecological considerations, but on a human-centered view of natural sites.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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