Bibliographic record
Abstract
On Canada Day 2017, author Helene Vosters hosted a Stitch-by-Stitch Unsettling Canada 150 sewing circle and picnic. Despite intermittent thundershowers, with umbrellas and soggy red thread in hand, a group of twenty to thirty intrepid stitchers embroidered text from the Truth and Reconciliation Commission of Canada’s (TRC) 94 Calls to Action onto Canadian flags. By the time Canada 150 reached its Canada Day zenith, Vosters asserts, it had already become increasingly apparent that the story of a beneficent Canadian nation committed to equity and multicultural inclusivity that the celebrations sought to engender had been significantly eclipsed in mainstream and social media by critiques of the sesquicentennial’s ahistorical premise and its disregard for the ongoing violent effects of settler-colonialism. Against this backdrop, Vosters weaves reflections of the sewing circle as a labour of reinscription with an inquiry into the value (and pitfalls) of embracing what Stó:lō scholar Dylan Robinson and settler scholar Keavy Martin call everyday “aesthetic actions.”
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.024 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".