Bibliographic record
Abstract
Archaeologically recovered material culture provides the crucial evidence for any long-term perspective on human activity. This chapter therefore grapples with the analytical challenges posed by the material record from Antikythera and then seeks to move beyond these and offer a wider history of island material culture. We begin by devoting methodological attention to the strengths and weaknesses of the archaeological record, particularly as collected by intensive surface survey, and build up a skeleton timeline of human activity on the island that provides a starting point for the two chronologically organised chapters that follow. As discussed in Chapter 2, the commentary provided later in the book can only hope to summarise briefly a considerable amount of focused artefact research whose primary publication is via a full digital catalogue and a series of specialist-led papers (referenced in detail later; see also Bevan and Conolly 2012a, 2012b for access to raw data). Following this chronological discussion, we then address a series of longitudinal, behavioural themes, such as the material culture of storage, transport, cooking, eating, drinking and conflict. A final section anticipates some of the broader concerns of later chapters by outlining ways in which Antikythera exhibits interestingly spiky patterns of both glut and scarcity in terms of its material resources. Again, we seek to place these observations in the wider behavioural context of how local communities have created, maintained and recycled their material world, particularly with regard to the themes of resettlement and recolonisation of landscapes that we first raised in Chapter 2.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.154 | 0.045 |
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".