Bibliographic record
Abstract
Research on the earliest habitation of Cyprus has largely been limited to the finds from excavation at a few sites, or gazetteer-style lists compiled from earlier surveys and fortuitous finds. Generally, though, there was little interest in finding and researching small lithic scatters and resource areas that may be of importance in unravelling the patterns of prehistoric land use. This thesis looks specifically at archaeological evidence from two research projects, the Canadian Palaipaphos Survey Project (CPSP) in southwest Cyprus and the Idalion Survey Project (ISP) in the central Troodos foothills. I focus on the distribution of, and the relationship between, large habitation sites, small, enigmatic lithic scatters and lithic resource areas. I support this with a study of ethnographic research on modern land use behaviour, and ethnoarchaeological research on the modern dhoukani (threshing sledge) industry. This latter is especially important as it sheds light not only on the locations and quality of numerous chert sources in both study areas, but documents modern behaviour in lithic acquisition, production and distribution, which may be crucial for understanding how lithic craftsmen worked in the past. During the course of my survey work, it became apparent to me that observer bias had a profound effect on the identification, collection and interpretation of the archaeological data. A major part of this thesis focusses on ways to identify and correct for a number of these types of biases. Taking into account these limitations on the results from the surveys, my research suggests that the early Neolithic inhabitants were not optimizing costs in lithic raw material selection, but were intentionally exploiting distant sources, despite having excellent quality sources much closer to their habitation sites. Based on the ethnographic and ethnoarchaeological studies, I suggest that this was the result of intentional strategies of risk management.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".