Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this article, we discuss a writing support strategy called Writing Office Hours (WOHs), which has been one of the offerings provided by the Robert Gillespie Academic Skills Centre (RGASC) at the University of Toronto Mississauga since the beginning of the COVID 19 pandemic in March 2020. WOHs evolved out of an earlier approach to course support known as Dedicated Drop-ins (DDIs), which were were made impossible due to the pandemic. In this article, we argue that these WOHs have had enthusiastic uptake by students (at least in part) because they help to break down some of the barriers—physical, logistical, psychological, and/or cultural—that can dissuade students from seeking out writing support. It is widely recognized that students do not always see writing centres as safe and welcoming spaces (e.g., Bond, 2019; Denny, 2010; Grutsch McKinney, 2013; Pregent, Williams, Marcyk, & Haywood, 2021). As we discuss below, because WOHs take writing support out of the centre and into students’ course shells, through its learning management system (LMS) (e.g., Brightspace), they help us reach students who might not (yet) see the writing centre as the “cozy” (Grutsch McKinney, 2013) place that we as writing centre faculty would like it to be.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it