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Record W3008810945 · doi:10.1080/10331867.2020.1721097

The Evolution of the Marshallese Vernacular House

2020· article· en· W3008810945 on OpenAlexaff
James Miller

Bibliographic record

VenueFabrications · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsVernacularVernacular architectureIndigenousDialecticHistoryArchitectureSociologyGeographyArchaeologyLiteratureArtEcologyEpistemologyPhilosophyBiology

Abstract

fetched live from OpenAlex

This paper investigates the vernacular architecture of the Marshall Islands through a deep-time perspective and demonstrates the Indigenous knowledge present in the production of the Marshallese vernacular house. The focus is on the socio-spatial patterns that represent generations of cultural knowledge and create culturally supportive built-environments, representative of living vernacular architecture. This article investigates the transformations of the Marshallese vernacular house through a diachronic study of habitation on the weto, which is the traditional system of land tenure through matrilineal inheritance. This study presents findings of extensive field work in the Marshall Islands investigating the dialectic relationship of Marshallese culture and its built-environment. To understand fundamental processes to the Marshallese production of space, a multi-sited case study design utilized theoretical replication to establish consistencies across rural, urban, and peri-urban communities. The study found that while manifestations of the Marshallese vernacular house evolve, the core processes remain consistent. The Marshallese vernacular house is a manifestation of generative processes, components of Indigenous knowledge. The Marshallese vernacular house is central to the Indigenous architecture of the Marshall Islands.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score0.742

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 studies0.0010.000
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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2020
Admission routes1
Has abstractyes

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