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Record W2909618460 · doi:10.1371/journal.pone.0209689

An analysis of network brokerage and geographic location in fifteenth-century AD Northern Iroquoia

2019· article· en· W2909618460 on OpenAlexaboutno aff
John P. Hart, Susan Winchell-Sweeney, Jennifer Birch

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFifteenthShoreGeographySocial network analysisGeopoliticsArchaeologySocial network (sociolinguistics)Economic geographyHistoryAncient historySocial mediaFisheryBiologyPolitical science

Abstract

fetched live from OpenAlex

Iroquoian villagers living in present-day Jefferson County, New York, at the headwaters of the St. Lawrence River and the east shore of Lake Ontario, played important roles in regional interactions during the fifteenth century AD, as brokers linking populations on the north shore of Lake Ontario with populations in eastern New York. This study employs a social network analysis and least cost path analysis to assess the degree to which geographical location may have facilitated the brokerage positions of site clusters within pan-Iroquoian social networks. The results indicate that location was a significant factor in determining brokerage. In the sixteenth century AD, when Jefferson County was abandoned, measurable increases in social distance between other Iroquoian populations obtained. These results add to our understandings of the dynamic social landscape of fifteenth and sixteenth century AD northern Iroquoia, complementing recent analyses elsewhere of the roles played in regional interaction networks by populations located along geopolitical frontiers.

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 score0.394
Threshold uncertainty score0.784

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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

Citations22
Published2019
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicHistorical and Cultural Archaeology StudiesFrench-language works237,207