Bibliographic record
Abstract
This chapter offers a plea for the media to reframe its coverage of campus controversies from free expression to academic freedom. These freedoms are entwined, but distinct. Freedom of expression is extended to all persons with no expectation of quality control, apart from legal prohibitions against defamation, threats, etc. By contrast, academic freedom is a cluster of freedoms afforded to scholarly personnel for a particular purpose – namely, the pursuit of universities’ academic mission to seek truth and advance understanding in the service of society. An academic freedom framing better reflects the distinctive social purpose around which universities are organized, as well as universities’ duty of care to employees and students. While universities have a legal and moral duty of care to all employees and students, the unjust, exclusionary past and present of higher education arguably makes that duty particularly acute in the case of equity-deserving (e.g., racialized, Indigenous, disabled or 2SLGBTQ+) people. Finally, academic freedom framing for campus media stories is less monolithic than free expression framing, allowing for a more nuanced understanding of campus controversies while keeping universities accountable to the public they serve. In this chapter, I survey three very different campus controversies at a single Canadian university, and the media response each received. I show how an academic freedom frame for those stories would have produced better reportage while reducing opportunities for bad actors to manipulate both universities and the media. At the end of the day, the real crisis at universities isn’t the cancellation of ill-judged events that were never a part of the academic mission; it is the ongoing erosion of academic freedom.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.072 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.011 |
| 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".