Canadian University Social Software Guidelines and Academic Freedom: An Alarming Labour Trend
Bibliographic record
Abstract
An analysis of first-stage social software guidelines of nine Canadian universities conducted in the 2012-13 academic year with the aim to reveal limits to academic freedom. Carleton University’s guidelines serve as the anchor case, while those of eight other institutions are included to signify a national trend. Implications for this work are central to academic labour. In as much as academic staff have custody and control of all records they create, except records created in and for administrative capacity, these guidelines are interpreted to be alarming. Across the guidelines, framing of social media use by academic staff (even for personal use) as representative of the university assumes academic staff should have an undying loyalty to their institution. The guidelines are read as obvious attempts to control rather than merely guide, and speak to the nature of institutional overreach in the related names of reputation (brand), responsibility (authoritarianism), safety (paternalistically understood and enforced), and the free marketplace of [the right] ideas.
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 | 0.034 | 0.097 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.023 |
| Science and technology studies | 0.027 | 0.025 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".