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Record W4396888350 · doi:10.35483/acsa.am.112.53

Storying Design Practice with Five Indigenous Design Paradigms

2024· article· en· W4396888350 on OpenAlexafffund
Honoure Black, Lancelot Coar, Shawn Bailey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsUniversity of Manitoba
FundersInfrastructure CanadaUniversity of Manitoba
KeywordsPraxisIndigenousSociologyEngineering ethicsActive listeningProcess (computing)Design thinkingComputer scienceEpistemologyEngineeringHuman–computer interaction

Abstract

fetched live from OpenAlex

How can design teaching and the design professions decolonize design practice and create a reciprocal praxis for both Indigenous and Non-Indigenous practitioners, students, and scholars? This is a question, as both Indigenous and settler scholars, we have begun to address through the development of a new methodological praxis with guiding paradigms. By embracing the concept of Anishinaabemowen, Gimiigiwemin, “we are exchanging gifts,” we prioritize listening to the land to ensure that our process considers place more thoroughly. This process-based design approach is intended to contribute to help guide both academic and professional design practices to engage more meaningfully with an expanded world view that prioritizes creating meaningful connections to the land. The Five Decolonizing Design Paradigms are rooted in land-based teaching initiatives through the Faculty of Architecture. These paradigms are ever developing, and are shared here through stories of projects that are guided through the teachings of: Danakamigad: it takes place, happens in a certain place; Andotan: listen for it and wait to hear it; Bawaajigan; a dream, a vision; Meshkwad: in turn, in exchange; and Naagotoon: make it show, reveal it. The intention of these paradigms and these experiences is that they may contribute to a path forward for the design disciplines as we collectively work towards truth and reconciliation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.887
Threshold uncertainty score0.473

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 science0.0000.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.368
Teacher spread0.312 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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