Bibliographic record
Abstract
This thesis examines how feminist ways of making and mending can be applied through a material investigation into postdisciplinary craft practices. Through practice-led research, material investigation and a conscious break from craft methods, I am embracing failure as a methodological framework. Some research motivations were guided by my own experience with influential women in my family. Through research and material investigations, craft practices were applied through a DIY method and were supported by sloppy craft theory. By embracing deskilling and reskilling within my work, I am investigating mending practices as a place for communal sharing and connection. \nBy embracing interdisciplinary approaches, craft and private practices are melded with sculptural and industrial metalworking, culminating in the form of plaster and bronze hands and tools. These solid, sculptural pieces of work are designed to capture gestures, the human form and the tools that created both embroidery and crochet pieces in this art practice. The exhibition was meant to be set in a recreated, imagined domestic space - to reflect women’s work and the rise of feminist craft practices in contemporary art. This space was envisioned to break away from the white cube and invite the viewer to share their knowledge and memories through an interactive "mend-in" session.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".