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Record W1566638349 · doi:10.7202/1025252ar

Building from the ground up: Reconstructing visions of community in Cambridge Bay, Nunavut

2014· article· en· W1566638349 on OpenAlexaffvenueabout
Brendan Griebel

Bibliographic record

VenueÉtudes/Inuit/Studies · 2014
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsGovernment of NunavutUniversity of Toronto
Fundersnot available
KeywordsVisionIdentity (music)ShamanismContext (archaeology)StorytellingBlueprintArchaeologySociologyPopulationHEROExcavationHAMLET (protein complex)HistoryAnthropologyVisual artsNarrativeAestheticsArtLiterature

Abstract

fetched live from OpenAlex

The Inuit qalgiq , or gathering house, once served as a forum for bringing communities together through acts of storytelling, drum dancing, shamanism, and the intergenerational transfer of knowledge. While the specific traditions associated with these structures have varied over time and space, they have remained of central importance to the affirmation of group identity and communal decision-making. In 2008, the excavation of an early Thule qalgiq near the Nunavut hamlet of Cambridge Bay provided a team of local participants and University of Toronto archaeologists with an opportunity to interpret the social position of the qalgiq in the context of a contemporary Inuit population currently struggling with issues of collective identity. This article presents a project originally designed to reconstruct a qalgiq as a museum exhibit with a structure drawn primarily from archaeological findings. By embedding the project in local understandings of history as a source for community wellness and revival, however, a different course was taken. While combining archaeological blueprints with contemporary realities and beliefs, the qalgiq was ultimately re-imagined as a venue in which ideas about community, both past and present, can be voiced.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.002
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 head0.120
GPT teacher head0.421
Teacher spread0.301 · 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 designQualitative
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

Citations5
Published2014
Admission routes3
Has abstractyes

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