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Record W4412870700 · doi:10.24908/pceea.2025.19655

Ethical and Sustainable Engineering Design: A Design for Conviviality Approach

2025· article· en· W4412870700 on OpenAlexaffvenue
Scott A.C. Flemming, Grant McSorley, Nebojsa Kujundzic

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsUniversity of Prince Edward IslandDalhousie University
Fundersnot available
KeywordsEngineering ethicsSustainable designArchitectural engineeringEngineeringSociologySustainabilityEcology

Abstract

fetched live from OpenAlex

(i) background: Various philosophers of technology argue against the common misconception that technology is neutral and simply serves human ends. “Reverse adaptation" is the idea that we create technologies to serve us, but, in the end it can often be the human that serves the machine. One key negative effect reverse adaptation is that it thwarts the human goal of sustainability. (ii) purpose: The aim of this paper is to explore an alternative design philosophy, “Designing for Conviviality,” that shows promise in addressing the above concerns. (iii) approach: In this paper a definition of conviviality is given along with its concomitant principles which can serve as a method of evaluating given tools, processes, and practices to aid in determining if they will have positive or negative societal and environmental consequences. (iv) outcomes: This research has resulted in an eight-point list as to the character of convivial tools and systems which enables the assessment of a given technology. (v) conclusions: Designing for Conviviality can serve as a way to guide design processes so that engineers can create products that will have a greater benefit to society and the environment.

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)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.853
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.033
GPT teacher head0.277
Teacher spread0.244 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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