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Record W3047162910 · doi:10.1386/9781789381801

Prototyping across the Disciplines

2021· book· en· W3047162910 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIntellect eBooks · 2021
Typebook
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)DisciplineSet (abstract data type)Rapid prototypingArchitectureComputer scienceWork (physics)EngineeringEngineering ethicsData scienceSoftware engineeringSociologyGeographySocial science

Abstract

fetched live from OpenAlex

If people from different fields are going to work together on projects, then they need to begin to understand each other. They can be separated by the words they use, the ways they work and how they think. However, in many fields there is common ground, in the attempts to create what is sometimes called inventive knowledge. These fields progress not only by understanding increasingly more about what already exists, but by making guesses about possible better futures. The guesses consist of small forays into that future, using strategies that are variously called learning through making, research through design or, more simply, prototyping. While traditionally associated primarily with industrial design, and more recently with software development, prototyping is now used as an important tool in areas ranging from materials engineering to landscape architecture to the digital humanities. This book collects current theories and methods of prototyping in a dozen disciplines, illustrating them through case studies of actual projects, whether in industry or the classroom. This edited collection aims to provide a context, a theoretical framework and a set of methodologies for interdisciplinary collaboration in design. Each chapter offers a different disciplinary perspective on prototyping, providing a case study as a point of comparison for identifying commonalities and divergences in current practices. Contributions are from a group of scholars with worldwide experience of working and presenting in design, and who are currently based in Canada, the United States, Chile and Brazil. This book isn’t just about design across the disciplines, it is about how prototyping works in different disciplines. Prototyping is a crucial part of the design process, and a practice used by creators from all design disciplines, from architects and engineers, to industrial and service designers, to test a concept or process and evaluate an idea. Much research has been published on prototyping in design; what makes this new book unique is the cross disciplinary nature, showing designers how they can learn from various approaches to improve their skills. Disciplines discussed include post-human design, theatre, tabletop game design, landscape architecture and arts entrepreneurship. Primarily of interest to design scholars and practitioners with an interest in integrative design. Undergraduates and graduate students in design, HCI (human-computer interaction) and the digital humanities. Textbook potential.

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.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.615
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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