Bibliographic record
Abstract
2022 has been a year of overlapping crises. The so-called “Freedom Convoys” paralyzing Canadian communities, the COVID-19 pandemic continuing to cause excess death and disability, the war in Ukraine, the intensifying effects of climate change, and increasing inflation have all signaled that we find ourselves in a new era, one that can be described as authoritarian capitalism. In this article, we view the restructuring of Canadian universities as yet another facet of authoritarian capitalism, which uses overlapping crises to further proletarianize library labour and fully subsume it into the “learning factory.” Using Sandro Mezzadra and Brett Neilson’s theorization of the politics of capital’s operations, we examine the library restructuring processes taking place at four Canadian universities: Alberta, Brock, Laurentian, and OCAD. We view the reorganizations taking place there as efforts on behalf of university administrators to use the intensification of global forces of capitalism to exploit academic librarian labour. Ultimately, we argue that Canadian librarians are witnessing both formal and real subsumption in Canadian universities, precipitated by the overlapping crises outlined earlier. As a result, we insist that librarians need to develop a politics of struggle to build collective consciousness and action in the face of authoritarian capitalism.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.032 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.040 | 0.015 |
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".