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Record W2791982557 · doi:10.3366/saj.2018.0093

Social organization in the Orcadian Neolithic: identification of elite domestic structures and settlements through analysis of excavation data

2018· article· en· W2791982557 on OpenAlexaff
David MacInnes

Bibliographic record

VenueScottish Archaeological Journal · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsNova Scotia Hospital
Fundersnot available
KeywordsHuman settlementArchaeologyExcavationEliteHistoryIdentification (biology)GeographyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.293
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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