Much More than Ecological Scale and 'Nature Knowing Best' Hiding in Environmental Decisions: A response to: Hull et al. 2002. 'Assumptions about Ecological Scale and Nature Knowing Best Hiding in Environmental Decisions'
Bibliographic record
Abstract
"Hull et al. (2002) have provided an interesting snapshot of ideas about 'nature' from a sampling of those involved in the science, policy, and management of forests in southwestern Virginia. Depending on the viewpoint, 'nature' is thought to be either delicately balanced, progressively evolving, and perfect, or dynamic, inefficient, and robust. Probably an equivalent sample anywhere in forested North America would disclose similar results. These opinions, split fairly evenly across the population, are the surface expression of two contesting minds: the preservationist and the interventionist."
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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.031 |
| Scholarly communication | 0.016 | 0.027 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.029 | 0.042 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".