Bibliographic record
Abstract
The social-ecological systems approach is one that recognizes the interactive nature of human-natural world activities, and thus recognizes in interdependence of people and nature. Its roots are said to be in the 1920s Chicago school of social or human ecology (cf. Berkes 2011 ), but that thinking focused on people and society, and incorporated the natural world only as a set of independent variables that influenced social structure (Steward 1955 ). More useful, in today’s threatened environments, is the way in which the construct has been developed by Fikret Berkes and others (Berkes and Folke 1998 ; Berkes et al. 2003 ) and tied to issues of complexity, panarchy (Gunderson and Holling 2002 ), and natural resource governance (Ommer and team 2008 ; Ommer 2010 ; Ommer et al. 2011 ). Social-ecological systems thinking, then, treats people and nature as one integrated biogeophysical unit. Such systems are complex and adaptive and delimited by the...
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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; both teacher heads agree on what is shown here.
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".