(Epistemic) Injustice and Resistance in Canadian Research Ethics Governance
Bibliographic record
Abstract
This article brings a philosophical perspective to bear on issues of research ethics governance as it is practiced and organized in Canada. Insofar as the processes and procedures that constitute research oversight are meant to ensure the ethical conduct of research, they are based on ideas or beliefs about what ethical research entails and about which processes will ensure the ethical conduct of research. These ideas and beliefs make up an epistemic infrastructure underlying Canada's system of research ethics governance, but, we argue, extensive efforts by community members to fill gaps in that system suggest that these ideas may be deficient. Our aim is to make these deficiencies explicit through critical analysis by briefly introducing the philosophical literature on epistemic injustice and ignorance, and by drawing on this literature and empirical evidence to examine how injustice and ignorance show up across three levels of research ethics governance: research ethics boards, regulations, and training. Following this critique, and drawing on insights from the same philosophical tradition, we highlight the work that communities across Canada have done to rewrite and rework how research ethics as a site of epistemic resistance is practiced.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.199 | 0.352 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.086 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".