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Record W6921867543 · doi:10.7298/x4736nw8

Crowding the Banks: The Historical Archaeology of Ohagi and the Post-Revolutionary Haudenosaunee Confederacy, ca. 1780-1826.

2017· article· en· W6921867543 on OpenAlexaboutno aff

Bibliographic record

VenueeCommons (Cornell University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSubsistence agricultureSettlement (finance)ExcavationColonialismHistorical archaeologyPrehistoryState (computer science)EthnohistoryPeriod (music)

Abstract

fetched live from OpenAlex

This dissertation examines the settlement pattern, housing styles, subsistence practices, and trade relationships of Haudenosaunee communities in New York State and Ontario in the post-Revolutionary era (1783-1826). Historical and ethnohistorical literature has described the period as one of despair, cultural loss, factionalism, and dependency among the Haudenosaunee Confederacy, and the communities have been labeled as “slums in the wilderness,” confined on small tracts of land and isolated from one another. My excavation at Ohagi, a Tuscarora village in Seneca territory in the Genesee River Valley (ca. 1780-1792), in combination with previously unanalyzed museum collections and a reevaluation of county histories and primary source documents, reveals that the Haudenosaunee communities in post-Revolutionary New York and Ontario built villages in a network of settlement complexes, encircling an area of rich natural resources and facilitating movement between communities and nations. The evidence reveals that housing styles did not immediately shift to European-style log cabins, as often assumed, and the shift to smaller houses did not necessarily accompany a change in matrilineal family structure and relationships. This dissertation employs recent literature on Settler Colonialism to critique both the exiting interpretations of the post-Revolutionary era as well as the practice of archaeological excavation of Native sites.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.008
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.036
GPT teacher head0.229
Teacher spread0.194 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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