Public and forest landowner attitudes towards longleaf pine ecosystem restoration using prescribed fire
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
Once dominant across the United States (US) Southeastern Coastal Plain, the longleaf pine (Pinus palustris Mill.) ecosystem covers a fraction of its historic geographic range. Restoration efforts have largely occurred on public lands, while most private forests feature alternative pine species. A better understanding of public interest in ecological restoration is critical to sustained efforts and successes. This research examines both forest landowner and general public interest in longleaf pine restoration. Results contribute to research on the social dimensions of ecological restoration, much of which has focused on small-scale projects rather than landscape-scale initiatives. In addition, this study addresses the lack of knowledge regarding factors driving attitudes towards ecological restoration other than demographic and psychometric variables. We employed a telephone survey of 2700 participants across eight states in the southeastern US in the historical range of longleaf pine. A majority of respondents supported restoration as a general goal and were supportive of the use of prescribed fire as a restoration practice. Place attachment, knowledge about longleaf pine, and age were among the significant predictors of restoration support. Findings have implications for future research focusing on sociocultural influences of restoration projects, as well as expanded public support for restoration of fire-maintained ecosystems.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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