“Nobody who can’t write can get a degree here”: The story of a Canadian university writing test
Bibliographic record
Abstract
We see our study as falling into the category of writing program historiography known as microhistory: a narrative reconstruction that explores in thorough detail a particular time period in a specific writing program’s history while striving to remain sensitive to the socially constructed attitudes of the primary actors. One of the signal values of microhistory for writing program scholars, Annie Mendenhall (2016, p. 40) writes, is that the reduced scale of analysis—from several decades or even longer to much narrower time frames—allows for close analyses of what actually shaped the actions of key stakeholders. Attending to the archival record while carefully monitoring our evaluations for preconceived assumptions creates opportunities for the examination of some of the meta-historical conclusions connected to master narratives in our field, the “myths” about which Dana Landry (2016) offers a thorough examination in her “people’s history” of Canadian Writing Studies. By critically analyzing the patencies and complications that existed between local and wider discourses underpinning writing pedagogy, such microhistories as the one we undertake here help reveal the “material and ontological” realizations of the ways that Landry’s broad myths continue to shape Writing Studies in Canada: that the teaching of writing is neither difficult nor scholarly; that all most struggling writers really need is a one-time remedial corrective course focused largely on grammar; and that writing is not worthy of serious academic attention (Landry, 2016, p. 63). Micro-histories respond to Bryant’s (2017, p. 17) call for “concrete research” that will help us to understand the etiologies of these tenacious meta-narratives, and in particular those that serve as warrants for the “complaints tradition” discussed by Heng Hartse (2018) during his keynote speech at the CASDW’s annual conference.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.116 | 0.040 |
| Scholarly communication | 0.021 | 0.006 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.010 | 0.023 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".