Pedagogical Over Punitive: The Academic Integrity Websites of Ontario Universities
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
This study is a snapshot of how Ontario universities are currently promoting \nacademic integrity (AI) online. Rather than concentrating on policies, this \npaper uses a semiotic methodology to consider how the websites of Ontario’s \npublicly funded universities present AI through language and image. The paper \nbegins by surveying each website and documenting emerging language-based \ntrends like interpellating different audiences, inducting students into \na larger scholarly community, and appealing to peer disapproval. The paper \nalso records how these websites visually communicate AI through images and \nvideo, arguing that image and text inform one another in a two-way relationship: \nfor example, a punitive image may undermine an otherwise textually \npedagogical website. Overall, the majority of Ontario websites have a decidedly \neducative mandate in their online AI resources, aligning with current AI \nscholarship that lauds education rather than after-the-fact punishment.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.216 | 0.000 |
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