Animal Ghosts at Canadian Universities: The Politics of Concealment and Transparency
Bibliographic record
Abstract
For many years, the lives of animals used for research in Canadian universities have been hidden from public view due both to physical concealment (e.g., security procedures and impenetrable labs) and administrative concealment (non-disclosure of information). Their lives unfold out of sight both physically and discursively, unavailable to the Canadian public for ethical consideration and democratic oversight. Recently, in response to calls by the public to end this secrecy, Canadian universities and the Canadian Council on Animal Care have embraced the language of "transparency" and have begun releasing documentation about animal research practices and procedures. This paper argues that this new "transparency" acts as its own kind of concealment practice, obscuring and displacing meaningful information while constructing highly selective ways of seeing animals in science, and manufacturing acquiescence/consent on the part of the public.
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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 | 0.028 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.054 | 0.067 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".