TOWARDS AN ARCHAEOLOGY OF SUSTAINABILITY: RESOURCE PACKAGES AND LANDSCAPE MANAGEMENT IN SPHAKIA, SOUTH-WEST CRETE
Bibliographic record
Abstract
Using evidence from the Sphakia Survey, a multiperiod archaeological project in south-west Crete, this article has two goals. The first is to contribute to a newly emerging field, the archaeology of sustainability. The investigation of sustainability in Sphakia uses five main kinds of evidence: environmental, archaeological/material, textual, oral, and patterns of activity that seem ‘difficult’ or ‘inconvenient’. Sphakia is a large area of highly dissected terrain with a wide altitudinal range – in many ways, a ‘tough’ landscape, where agropastoralism has been its main economy. The second goal is to introduce the concept of a Resource Package (RP), a combination of perceived resources in an area, as an analytical tool for landscape study. Evidence for identifying agropastoral RPs of various scales, used at a particular time, includes imports, such as pottery and obsidian, which can suggest exchange for a local resource or product; sacred sites; coins; texts and inscriptions; place-names and other toponyms; and maps. The concept of RPs can usefully be applied synchronically and diachronically to multiperiod projects like this, as well as more generally to other landscapes, ‘tough’ or not. Sustainable strategies (that is, maximising resources and RPs without exhausting them) were used in the Prehistoric, Graeco-Roman and Byzantine–Venetian–Turkish epochs in Sphakia; some may be relevant for the future.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".