Reconfiguring the Academic Dance: A Critique of Faculty’s Responses to Administrative Practices in Canadian Universities
Bibliographic record
Abstract
This article explores and critiques Canadian academics’ responses to new administrative practices in a variety of areas, including resource allocation, performance assessment and the regulation of academic work. The main argument is that, for the most part, faculty are responding to what administrative practices appear to be, rather than to what they do or accomplish institutionally. That is, academics are seeing and responding to these practices as isolated developments that interfere with or add to their work, rather than as reorganizers of social relations that fundamentally transform what academics do and are. As a result, their responses often serve to entrench and advance these practices’ harmful effects. This problem can be remedied by attending to how new administrative practices reconfigure institutional relations in ways that erode the academic mission, and by establishing new relations that better serve academics’—and the public’s—interests and needs. Drawing on the work of various academic and other activists, this article offers a broad range of possible strategies to achieve the latter goal. These include creating faculty-run banks to transform the allocation of institutional resources, producing new means and processes to assess—and support—academic performance, and establishing alternative policy-making bodies that operate outside of, and variously interrupt, traditional policy-making channels.
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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.085 | 0.099 |
| Scholarly communication | 0.026 | 0.006 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".