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Record W3158261648 · doi:10.1017/aaq.2021.5

Conflict, Population Movement, and Microscale Social Networks in Northern Iroquoian Archaeology

2021· article· en· W3158261648 on OpenAlexaboutno aff
Jennifer Birch, John P. Hart

Bibliographic record

VenueAmerican Antiquity · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsRelocationCoalescent theoryPopulationGeographyArchaeologySettlement (finance)ShoreMicroscale chemistryHuman settlementSocial organizationEconomic geographyGeologyBiologyOceanographySociologyDemographyAnthropology

Abstract

fetched live from OpenAlex

We employ social network analysis of collar decoration on Iroquoian vessels to conduct a multiscalar analysis of signaling practices among ancestral Huron-Wendat communities on the north shore of Lake Ontario. Our analysis focuses on the microscale of the West Duffins Creek community relocation sequence as well as the mesoscale, incorporating several populations to the west. The data demonstrate that network ties were stronger among populations in adjacent drainages as opposed to within drainage-specific sequences, providing evidence for west-to-east population movement, especially as conflict between Wendat and Haudenosaunee populations escalated in the sixteenth century. These results suggest that although coalescence may have initially involved the incorporation of peoples from microscale (local) networks, populations originating among wider mesoscale (subregional) networks contributed to later coalescent communities. These findings challenge previous models of village relocation and settlement aggregation that oversimplified these processes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.274
Threshold uncertainty score0.544

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.367
Teacher spread0.341 · 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 source (direct Gemma or distilled Codex), 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

Citations17
Published2021
Admission routes1
Has abstractyes

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