"Without trust, research is impossible": Administrative inertia in addressing legal threats to research confidentiality
Bibliographic record
Abstract
The last two decades have seen the development of formalized federal research ethics policies in countries such as the US, Canada, Australia, and New Zealand. The focus of these policies has been researchers; comparatively little attention has been paid to the university administrations who provide the context in which those review bodies operate and whose resources are integral to protecting research participants when external threats arise. Far from being staunch defenders of academic freedom and protecting those who participate in research, university administrators in Canada have more commonly revelled in "edgy" research until the subpoena arrives, and then promptly thrown the researchers under the proverbial bus. In Canada, the federal ethics policy now requires university administrations to "support" their researchers when a legal threat arises, and "encourages" them to have policies in place that articulate how they will do so. Two years later, few policies exist. This thesis will review the record of administrative support for cases where research confidentiality is threatened, and present the results of a national survey of REB chairs, administrators, and REB staff, as to the current state of these policies and the impediments to their creation.
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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 | 0.291 | 0.445 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.027 | 0.059 |
| Scholarly communication | 0.043 | 0.031 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.009 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".