Social organization in the Orcadian Neolithic: identification of elite domestic structures and settlements through analysis of excavation data
Bibliographic record
Abstract
The nature of social organization during the Orcadian Neolithic has been the subject of discussion for several decades with much of the debate focused on answering an insightful question posed by Colin Renfrew in 1979. He asked, how was society organised to construct the larger, innovative monuments of the Orcadian Late Neolithic that were centralised in the western Mainland? There are many possible answers to the question but little evidence pointing to a probable solution, so the discussion has continued for many years. This paper takes a new approach by asking a different question: what can be learned about Orcadian Neolithic social organization from the quantitative and qualitative evidence accumulating from excavated domestic structures and settlements? In an attempt to answer this question, quantitative and qualitative data about domestic structures and about settlements was collected from published reports on 15 Orcadian Neolithic excavated sites. The published data is less extensive than hoped but is sufficient to support a provisional answer: a social hierarchy probably did not develop in the Early Neolithic but almost certainly did in the Late Neolithic, for which the data is more comprehensive. While this is only one approach of several possible ways to consider the question, it is by exploring different methods of analysis and comparing them that an understanding of the Orcadian Neolithic can move forward.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.018 | 0.025 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".