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Record W3110838221 · doi:10.35784/odk.2085

Rekonstrukcja rdzennego dziedzictwa architektonicznego

2020· article· en· W3110838221 on OpenAlexaffabout
Nancy Mackin

Bibliographic record

VenueProtection of cultural heritage · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsArchitecturePrideEnthusiasmConstruct (python library)IndigenousResource (disambiguation)HistoryGeographyArchitectural engineeringEngineeringPolitical scienceEcologyArchaeologyComputer sciencePsychologyLaw

Abstract

fetched live from OpenAlex

Long resident peoples including Gwich’in, Inuvialuit, Copper Inuit, and Sami, Coast Salish and others have learned over countless generations of observation and experimentation to construct place-specific, biomimetic architecture. To learn more about the heritage value of long-resident peoples’ architecture, and to discover how their architecture can selectively inform adaptable architecture of the future. we engaged Inuit and First Nations knowledge-holders and young people in reconstructing tradition-based shelters and housing. During the reconstructions, children and Elders alike expressed their enthusiasm and pride in the inventiveness and usefulness of their ancestral architectural wisdom. Several of the structures constructed during this research are still standing years later and continue to serve as emergency shelters for food harvesters. During extreme weather, the shelters contribute to a potentially widespread network of food harvester dwellings that would facilitate revitalization of traditional foodways. The reconstructions indicate that building materials, forms, assembly technologies, and other considerations from the architecture of Indigenous peoples provide a valuable heritage resource for architects of the future.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0030.002
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0210.003

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 head0.150
GPT teacher head0.239
Teacher spread0.090 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations1
Published2020
Admission routes2
Has abstractyes

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