8 Survey and landscape archaeology in Greece in the twenty-first century
Bibliographic record
Abstract
Over 100 archaeological survey projects – of various kinds – have taken place in Greece over the last quarter century, making it one of the most intensively studied countries in Europe from the perspective of landscape archaeology, defined by various types of interest in settlement patterns and human–environmental interaction at spatial scales beyond the individual site. This article examines the practice of survey archaeology in Greece over the last 25 years, with a particular focus on projects that have taken place in the last 10 years. More broadly, it presents large-scale trends in surveys since their coalescence as a systematic form of archaeological research in the late 1950s, based on a dataset of 204 individual projects, mapped and classified according to type, spatial scale, methods, and chronology. Surveys in the twenty-first century exhibit considerable variety in methods and goals, with many characterized by smaller spatial scales, the integration of various types of remote sensing, and a focus on archaeological sites; we see fewer of the large-scale, diachronic regional surveys that became widespread in the later twentieth century. This variety – along with the increasing production and availability of high-quality, multi-modal data – should be applauded, though regional analysis remains a critical strength and important goal for landscape archaeologists in Greece. Lingering problems include publication lag, digital data availability and interoperability, and (occasional) over-emphasis on methodology as an end in and of itself, sometimes at the expense of historical and anthropological research questions. Promising developments for the future concern: (1) the investigation of landscapes that have received little attention from systematic surveys (highlands, mountains, forests, uninhabited islands), especially via remote sensing; (2) the publication, reanalysis, and interpretation of ‘legacy’ datasets; and (3) the integration of survey datasets across multiple scales to address ‘big-picture’ questions in the history and archaeology of Greece, as well as themes of wider significance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".