Understanding Adaptive Capacity in Forest Governance: Editorial
Bibliographic record
Abstract
"The term adaptive capacity has often been used to indicate the role that various factors may play in determining the extent to which adaptation to climate change - different actions to deal with the consequences of climate change - is possible. While the focus on adaptive capacity has been pronounced within climate change literature, this literature strongly acknowledges that adaptation will not take place with regard to climate change alone. Adaption to climate change should rather be seen in the context of adaption to all other coexisting stressors, or what has been called double or multiple impacts. The social, economic and political situation thus plays a part in determining whether environmental impact or exposure will result in vulnerability and in consequences on the ground. For instance, a flood will only become a disaster if the preparedness needed to deal with the consequences of flooding does not exist. The adaptive capacity or resources to deal with the risk of flooding, such as the existence of emergency plans and the existence of funding and personnel, are crucial."
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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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".