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Record W7053212290

The three dimensions of inclusive design: A design framework for a digitally transformed and complexly connected society

2018· other· en· W7053212290 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2018
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSociotechnical systemAffordanceField (mathematics)Scope (computer science)Capability approachDesign methodsUniversal designDesign educationLeverage (statistics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis attempts to answer the following meta-design challenge: In this digitally transformed and increasingly connected society, how can we design in such a way that we include the full range of human diversity? How can we use design to both circumvent the new barriers that escalate exclusion and leverage the new affordances of emerging sociotechnical systems to reduce disparity? \n \nThis thesis documents the formulation, application and testing of a guiding framework for Inclusive Design, suitable for a digitally transformed and increasingly connected context. During the course of my doctoral studies I have iteratively formalised and refined this framework. As a doctoral student, Founder/Director of the Inclusive Design Research Centre of Canada (1993–), and co-Director of the sister European lab, the Inclusive Design Research Centre of Ireland (2008–), I have implemented the inclusive design framework in applied research with colleagues. I have also taught the framework in the graduate programme that I launched at OCAD University in Toronto in 2011. These framework applications have helped to develop tools and design methods that support the framework. The thesis conveys the formulation, implementation, and communication of the framework to several application domains. \n \nThe fields of knowledge are diverse and post-disciplinary. If a primary field must be chosen, then it would be the field of Design, not only in terms of Design Engineering but also in the broader scope of Design for Society: both are explored and developed in tandem. But the impact of the work in the ‘real world’ and within the industry sector that can support community change, is the most important aim and contribution of this research. The evolving framework is already being applied by a global collaborating community and has formed the basis of the corporate transformation of companies such as Microsoft. The applied research has delved into many cognate fields, including Systems Thinking, Deeper Learning, Economics, Machine Learning, Human Computer Interfaces, and Critical Disability Studies. \n \nThe thesis makes an original and substantial contribution to knowledge, articulating a guiding framework for Inclusive Design in a digitally transformed and complexly connected global society. The framework applies Systems Thinking to the area of digital inclusion for people experiencing disabilities and adds the consideration of the design process to inclusive or accessible Design. Examples taken from years of intensive practice that support the thesis are provided as use cases, to support future research and implementation. \n \nThe thesis also attempts to provide a bridge between scholarly study and community action, in part by using clear language to prevent or overcome any conceptual divide between scholars and the diverse individuals who must participate in co-designing a more inclusive society. The thesis includes translations of the concepts inherent in the proposed framework, expressed clearly and succinctly, for a variety of co-designers. The thesis posits that Diversity is Strength: a concept that can be applied in many cognate fields as well.

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)0.031
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0090.062
Scholarly communication0.0200.021
Open science0.0040.015
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0060.001

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 head0.063
GPT teacher head0.309
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2018
Admission routes1
Has abstractyes

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