MétaCan
Menu
Back to cohort
Record W7135161874

Engaging With Non-Human Perspectives Through Embodied Design Practices

2023· article· en· W7135161874 on OpenAlexaff
Michaela Honauer

Bibliographic record

VenueUniversity of Twente Research Information · 2023
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsEmbodied cognitionNegotiationAgency (philosophy)Process (computing)Design processIntervention (counseling)Engineering design processThrough-the-lens metering
DOInot available

Abstract

fetched live from OpenAlex

More-than-human perspectives become increasingly important with the growth of global challenges and the intervention of autonomous technologies. Research has elaborated on the rationale for more-than-human-centred design approaches but still needs more practical guidance to embody non-human perspectives in the design process. This paper addresses embodied co-creation practices that enable the involvement of human and non-human actors in the design process. The estrangement framework provides a lens for comparing three examples from the literature. The evaluation of these three different co-creation projects reveals considerations on how to alter the human way of designing to be more inclusive of non-human perspectives. In this process, relationships and agency between human and non-human co-creators dynamically change and unfold. Their entanglements impact the collaborative design process in different ways. Humans and non-humans’ diverse perspectives and vulnerabilities become transparent and facilitate the negotiation of their individual values and needs. Embodied design practices can translate the theoretical considerations made in this paper into tangible design activities. The performing arts could provide a laboratory to experiment with such co-creation processes through artistic means—to understand better non-human perspectives and how humans and non-humans co-shape their relationships in and with the world.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.857
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.008
Open science0.0010.000
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 head0.139
GPT teacher head0.392
Teacher spread0.253 · 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 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 venueUniversity of Twente Research InformationSame topicInnovative Human-Technology InteractionFrench-language works237,207