MétaCan
Menu
Back to cohort
Record W6936382886 · doi:10.57698/v16i3.05

Exploring the Composite Intentionality of 3D Printers and Makers in Digital Fabrication

2022· article· en· W6936382886 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicCrafts, Textile, and Design
Canadian institutionsOntario College of Art and DesignSimon Fraser UniversityUniversity of Victoria
Fundersnot available
KeywordsIntentionalityWork (physics)Key (lock)Component (thermodynamics)Composite number

Abstract

fetched live from OpenAlex

In this paper, we identify new relationships between technologies and people in the context of digital fabrication. Our research applies a postphenomenological lens to understand and identify such relationships by using the concept of intentionality, an idea that relates to how humans and technologies, in their corporeal sense, direct themselves at the world rather than their purpose of action. We conducted a study wherein we first modified four 3D printers that highlight technological intentionality by either reducing, redirecting, reshaping, or redistributing the CAD model and filament of a given print. Next, experienced makers were invited to print models with one of four printers and reflect upon the effects of the coupling between their intentionality and that of the 3D printer. We contribute descriptions for new ways to frame human-technology relationships within the context of digital fabrication and highlight three relationships with machines: anticipatory, itineration and resistance, and their implications.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience 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: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.208
GPT teacher head0.275
Teacher spread0.066 · 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