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Record W196763271 · doi:10.15760/etd.502

Rebuilding the Architectural History of the Fort Vancouver Village

2000· report· en· W196763271 on OpenAlexaboutno aff
Meredith Mullaley

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHuman settlementArchitectureArchaeologyGeographyVernacularColonialismVernacular architectureHistoryLate 19th centuryEthnologyArtPeriod (music)

Abstract

fetched live from OpenAlex

In the mid-19th century, the Fort Vancouver employee Village was one of the most diverse settlements on the Pacific Coast. Trappers, tradesmen, and laborers from Europe, North America, and Hawaii worked and lived within a highly stratified colonial social structure. Their homes have been the site of archaeological research for nearly 50 years, but the architectural features and artifacts have received limited attention. Inspired by an 1845 description of the Village that described houses that were "as various in form" as their occupants, this study examined community-level social relationships in this 19th-century fur trade community through vernacular architecture and landscape. This thesis presents the life histories and layouts of five Village houses. The architectural analysis relied on data from features, square nails, window glass, and bricks. The resulting architectural interpretations were synthesized to explore the larger vernacular landscape of the Village and investigate whether the house styles reflect processes of creolization and community development, or distinction and segregation among the Village residents. The houses all stem from a common French-Canadian architectural tradition, built by the first employees at Fort Vancouver, but the life histories also revealed that the houses were occupied (and repaired) by a second wave of employees at some time during the 1840s. A reminder that Village houses deposits may reflect multiple owners, and should not be conceptualized as the result of a single household. Finally, this thesis demonstrates that nuanced architectural data that can yet be learned from past excavation assemblages when the many nails, bricks, and window glass specimens are reanalyzed using current methods.

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)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.124
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.285
Teacher spread0.243 · 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
GenreOther

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

Citations10
Published2000
Admission routes1
Has abstractyes

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