Introduction to the Special Section of Conference Proceedings from the 2018 Canadian Writing Centres Association
Bibliographic record
Abstract
In this special section of the Canadian Journal for the Study of Discourse and Writing/ Rédactologie (CJSDW/R), we are pleased to share three articles that were originally presented at the 2018 Canadian Writing Centres Association / L’Association canadienne des centres de rédaction (CWCA/ACCR) conference in Saskatoon, Saskatchewan. This introduction situates those articles within the context of the work of other writing centre scholars and practitioners at the conference. The 2018 CWCA conference call invited attendees to share and explore ways that we, as writing centre practitioners, can engage in anti-oppressive educational practices. 1 Participants in the conference took up the invitation to explore the 2018 theme, “Politics and the Writing Centre: Inquiry, Knowledge, Dialogue, and Action,” in many ways. In general, though, four main themes were evident throughout the conference: Indigeneity and decolonization, the politics of space, identity, and labour.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.169 | 0.045 |
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".