The Social-Ecological Keystone Concept: A Quantifiable Metaphor for Understanding the Structure, Function, and Resilience of a Biocultural System
Bibliographic record
Abstract
Social-ecological system theory draws upon concepts established within the discipline of ecology, and applies them to a more holistic view of a human-in-nature system. We incorporated the keystone concept into social-ecological system theory, and used the quantum co-evolution unit (QCU) to quantify biocultural elements as either keystone components or redundant components of social-ecological systems. This is done by identifying specific elements of biocultural diversity, and then determining dominance within biocultural functional groups. The “Hawaiian social-ecological system” was selected as the model of study to test this concept because it has been recognized as a model of human biocomplexity and social-ecological systems. Based on both quantified and qualified assessments, the conclusions of this research support the notion that taro cultivation is a keystone component of the Hawaiian social-ecological system. It further indicates that sweet potato cultivation was a successional social-ecological keystone in regions too arid to sustain large-scale taro cultivation, and thus facilitated the existence of an “alternative regime state” in the same social-ecological system. Such conclusions suggest that these biocultural practices should be a focal point of biocultural restoration efforts in the 21st century, many of which aim to restore cultural landscapes.
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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 | 0.000 | 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 | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".