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Record W2313306792 · doi:10.11141/ia.18.1

Using Computer Modelling and Virtual Reality to Explore the Ideological Dimensions of Thule Whalebone Architecture in Arctic Canada

2005· article· en· W2313306792 on OpenAlexaffabout
Peter Dawson, Richard Levy

Bibliographic record

VenueInternet Archaeology · 2005
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsArchitectureIdeologyArcticVirtual realityThe arcticComputer scienceHuman–computer interactionSociologyGeographyArchaeologyGeologyOceanographyPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Arctic archaeologists have long suspected that the whalebones used to construct semi-subterranean winter houses by Thule culture peoples were symbolically resonant. These assumptions are based on observations of the non-utilitarian use of jaw bones and crania in Thule house ruins, and ethnographic descriptions of architectural symbolism relating to the whale hunt in Historic Alaskan Inupiat houses. In this paper, we use a 3-dimensional computer reconstruction of a semi-subterranean whalebone house to search for visual expressions of whaling-related ritual in Thule architecture. Results suggest that the whalebone superstructure may have been designed to evoke important themes when viewed from specific locations within the house, and under different lighting conditions. These themes, which appear in Inupiat myths and stories, involve the belief that women transform houses into living whales during the time of the hunt. This article will particularly interest: * Archaeologists, anthropologists, and architects interested in indigenous architecture, computer modelling, and virtual reality * Those interested in architectural symbolism Key points: * Arctic prehistory * Thule whalebone houses * Symbolic usage of whalebone in house construction

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.352

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.111
GPT teacher head0.362
Teacher spread0.251 · 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 designSimulation or modeling
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
Published2005
Admission routes2
Has abstractyes

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