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Record W7060885798

Oral Traditions and the Archaeological Record of a Wabanaki Maritime Society

2007· article· en· W7060885798 on OpenAlexaboutno aff

Bibliographic record

VenueDigiNole (Florida State University) · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsWatercraftPrehistoryArchaeological recordIndigenousOral historyExcavationOral traditionPrehistoric archaeologyMaritime archaeology
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines prehistoric watercraft documented in the region now inhabited by the Wabanaki, an indigenous maritime society living in New England and the Canadian Maritimes, from archaeological and oral traditions perspectives.Archaeological research has been slow to accept oral traditions as valid, independent sources of evidence.The paucity of prehistoric watercraft and associated tool kits in this study requires exploring Wabanaki prehistory through alternative sources.I gathered oral traditions from a St. Francis Abenaki elder, a Wabanaki oral historian and storyteller, and a traditional Wabanaki canoe artist to tie together historical and archaeological data using maritime socio-cultural relations in the form of oral traditions and histories.Watercraft remains have not been preserved in the archaeological record, requiring an alternative approach, defined within the parameters of this thesis as an oral traditions methodology, to study the maritime technological adaptations of the Wabanaki.This methodology may serve as a template for similar archaeological studies, historic and prehistoric, within societies that value the accurate transmission of oral traditions in the absence, as well as presence, of material remains.In particular, I aim to facilitate a better understanding of Wabanaki technology within the maritime environment of New England and the Canadian Maritimes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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 designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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