Material Matters: Lowering barriers to uptake, Diversifying range of application, Carrying forward legacy processes.
Bibliographic record
Abstract
New production technologies and modes of enterprise based on proprietary and cost-effective, open-source production platforms are changing the nature of making. An exemplar of this change, 3D Printing has created a rapidly developing presence as an emergent production technology across many sectors. As this technology's development continues, artists and designers are no longer constrained by traditional models of form development and production: accessible 3D technology stands to markedly revise a broad range of legacy production practices.Material Matters - a research cluster within the Intersections Digital Studios of the Emily Carr University of Art and Design - is exploring these new digital technologies as a viable analogue to traditional methods and materials. As 3D printing becomes less expensive, more powerful and more pervasive it diffuses into a wider range of opportunities. As these new means of creative production emerge they intersect with established practice, Material Matters examines these points of contact with an emphasis on four interrelated components: material development and lateral application; and commercial application and partnership. This paper will highlight elements of these four streams.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".