Resilience Thinking and Landscape Complexity in the Basentello Valley (BA, MT), c. AD 300–800
Bibliographic record
Abstract
Archaeological data for the transformation of late Roman rural landscapes in Southern Italy over the sixth to eighth centuries AD are often meagre. This record often provides little explanatory power in the context of understanding the collapse of Roman political and economic hegemony and the framework for the regeneration of these relationships in the early medieval countryside. Resilience thinking offers a robust suite of heuristics to help guide both method and theory in understanding the key socio-environmental relationships involved in this transformative process based on limited material evidence. Through insights gained from developing a panarchic perspective of the Basentello landscape between AD 300 and 800, both capacities for and strategies of resilience to landscape-scale shocks and stressors emerge as key patterns in this collapse process. To explain how these patterns emerge, resilience thinking employs narratives from complexity science by framing landscapes as self-organizing complex adaptive systems. It is through appreciating this complexity that archaeologists can revolutionize how we understand landscape-scale transformations, the role of resilience in landscape history and, more broadly, the nature of societal collapse.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".