MétaCan
Menu
← Back to cohort
Record W4384696235 · doi:10.22215/etd/2023-15608

The Resilient Nature of Inuit Knowledge: Community, Culture and Climate Adaptation

2023· dissertation· en· W4384696235 on OpenAlexaboutno aff
Natasha Lemire-Waite

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsHuman settlementSubsistence agricultureVitalityArcticTypologyPsychological resilienceGeographyIdentity (music)SustainabilityAdaptation (eye)Political scienceEnvironmental ethicsEthnologySociologyArchaeologyEcologyAgricultureAesthetics

Abstract

fetched live from OpenAlex

This thesis explores the design of a refined building typology informed by Inuit ways of knowing, doing, and making – innovating through the wisdom and experience of Inuit. A ‘resilience center’ responds to the need for culturally appropriate and sustainable infrastructure within the Canadian Arctic, drawing from traditional Inuit knowledge supplemented by experimental materials and technologies to equip Inuit in a changing landscape. Since the arrival of early Settlers across the North, including the imposition of their foreign assemblies and settlements, Euro-Canadians have displaced Inuit societies from their homelands and customary ways of life, and consequently altering Inuit nomadic lifestyles centered on subsistence and cultural sustainability. Amidst a myriad of social, cultural, economic, and ecological forces, today’s Inuit communities continue to find ways to balance ‘old’ and ‘new’. By sustaining and strengthening Inuit culture, a ‘resilience center’ supports Inuit in ensuring the vitality of their culture and identity.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.019
Scholarly communication0.0110.005
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.041
GPT teacher head0.423
Teacher spread0.382 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicIndigenous Studies and Ecology→French-language works237,207→