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Record W7135159542

Futuring: Toward a more inclusive and empathetic approach

2023· article· en· W7135159542 on OpenAlexaff
Emily MacLoud, Ashleigh West

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2023
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsImpermanenceMeaning (existential)Scope (computer science)NarrativeFutures contractAmbiguityMindfulnessPosition (finance)
DOInot available

Abstract

fetched live from OpenAlex

In a world marked by rapid and constant change, societies are grappling with transitions like never before. Designers are often at the forefront of this change, navigating ethical implications and confronting uncomfortable truths while interacting with individuals holding differing opinions to drive meaningful change. This article delves into the designer’s responsibility to be aware of their character and position in “design defuturing,” meaning their influence on negating certain futures. The authors provide experiences of narrowing the scope in design projects through speculative scenarios and reflect on the implications of this practice. The article also offers the potential of mindfulness and Buddhist frameworks and ideas to guide designers toward creating futures and producing design fictions that are egoless, detached from outcomes, and recognise impermanence and the interdependence of all beings. These practices help designers to enact “contra-innovation” and challenge the dominant narratives and actions of innovation that defuture. The concept of non-self challenges designers to go beyond their individual perspectives and ego-driven design approaches. It helps designers to step outside of themselves and better connect with the people and planet they are designing with and for. This encourages a more inclusive, adaptable, and empathetic approach that aligns with the principles of human-centred and sustainable design.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0040.005
Research integrity0.0000.001
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 head0.082
GPT teacher head0.333
Teacher spread0.251 · 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 designTheoretical or conceptual
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

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