Threaded together: An arts-based inquiry into the design processes of a team of graduate students working on a professional development infrastructure for teachers in the Anglophone sector in Québec
Bibliographic record
Abstract
In an attempt to link my art practice with my educational research practice, and in the spirit of reflective practice, I wanted to create a quilt that would act as a vehicle for reflection on our experiences as a design team while developing a flexible learning network for teachers. What I was attempting to do is to use quilting as a metaphor for our process but also use quilting as a research methodology. The use of quilting as a metaphor afforded me a way to view our design efforts in a way that I had not been able to see or express until that moment. The purpose of using quilting as a metaphor in this inquiry was that I thought it could provide an alternative language for exploring what seemed 'natural' about our way of working. In this sense, what we commonly understand about the instructional design process is supplanted by an alternative vision. The quilt that I created serves as a multi-vocal visual narrative that represents important events, ideas and themes that were identified by the participants in the inquiry and that emerged from my analysis of the data. The quilt offers a site for these co-constructed narratives to be told. There are no right or wrong answers, there are multiple truths that were gathered and shared. I see the quilt as a reflexive intertextual space for conversation, interpretation, and critique of our design practices.
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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.021 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".