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Record W7138118241 · doi:10.51270/48.1.037

A Revised Chronology for the Emergence and Expansion of Late Woodland Villages along the North Shores of Lake Erie and Lake Ontario and Evidence for a Rapid Increase in Fortified Settlements in the Thirteenth Century AD

2024· article· W7138118241 on OpenAlexvenueaboutno aff
James Conolly, William Fox, Jennifer Birch

Bibliographic record

VenueCanadian Journal of Archaeology · 2024
Typearticle
Language
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChronologyWoodlandHuman settlementContext (archaeology)ShoreRadiocarbon datingPrehistory

Abstract

fetched live from OpenAlex

In this paper, we present a revised chronology for the appearance and development of village communities dating to the first part of the Late Woodland across the north shores of Lake Erie and Lake Ontario (Ontario, Canada). Our work is based on a sample of existing and newly obtained accelerator mass spectrometry (AMS) dates from Late Woodland sites dating before AD 1450. We have examined these within a Bayesian modelling framework to provide a more precise understanding of the timing and pace of cultural change, with a focus on the changes in settlement size and organization structure. Our results emphasize the longevity and adaptive success of low-level food production among communities along the Grand River in the first phase of the Late Woodland. We also show that the transition to palisaded villages and fortified towns was not a slow four-century-long process that conventional dating implied. Instead, these changes unfolded over 150 years, exhibiting a more rapid transition than has previously been recognized, concentrated in the thirteenth century AD. These results are interpreted within the context of the growing value of intra-community cohesion alongside evidence for inter-community conflict.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
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 head0.040
GPT teacher head0.285
Teacher spread0.245 · 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.

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

Citations0
Published2024
Admission routes2
Has abstractyes

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