A review and synthesis of social indicators for sustainable forest management
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
This review synthesizes some of the main themes of social sustainability indicators for forest management, and addresses conceptual categories, issues, and limitations associated with the use of social indicators. Socio-cultural values and conditions associated with quality of life, public access to non-market benefits and resources, governance, and community stability are discussed. The paper illustrates how a selection of social indicators has been prescribed and used within various sustainable forest management (SFM) systems of criteria and indicators (c&I) at different scales from the international to the local in British Columbia. Social indicators are, in general, weakly developed relative to ecological and economic indicators. Standard c&I systems often omit crucial social indicators, or include them without specific definitions or measurable benchmarks. Recommendations are made for future research that examines the fundamental nature of social indicators and their underlying cause-and-effect relationships, and supports improved methods and tools for integrating social indicators into forest management and decision making. The role of forestry in contributing to broader social indicators, such as sense of place and community cohesion, needs to be clarified.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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