Bibliographic record
Abstract
A soft felt logic is a textile exploration situated in the ‘soft felt’ experience, one which questions, prioritises, and plays with the sense of touch. I posit that this soft felt logic methodology can make sense of how touch - through tactile/textile experiences - is grounded in embodied action. I focus on the areas of “Touch, Colour, and Space” to explore the subject matter. The accompanying show hands holding, holding held at Ignite Gallery, Toronto displays a series of wall and floor-based hand-woven forms that present an invitation to feel. Through the development of these forms, I ask how the use of material creates visual and physical textures that stimulate a yearning to touch both for the perceiver and myself as the maker. To this end, what is this yearning? Through close material study, I look at factors like scale, pattern, placement, fibre, and colour to understand the impact of my designs and their relationship to a soft felt logic. Through the development of these forms, I investigate how colours, tones, and hues create dialogue and interactions that incentivise the perceiver to touch. Will distortion through colour selection impact the ability for a multi- or merged-sensorial experience of perception? I investigate the world around me, what spaces do craft objects occupy? Can building a soft felt logic create space for new methods of textile interaction to emerge? In touching these works, can a greater understanding and appreciation for the tactile/textile body emerge? I identify as a maker/craft practitioner, and this influences the methods I use within my making and research; it’s situated on the loom and betwixt my hands.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".