Ethics review and freedom of information requests in qualitative research
Bibliographic record
Abstract
Freedom of information (FOI) requests are increasingly used in sociology, criminology and other social science disciplines to examine government practices and processes. University ethical review boards (ERBs) in Canada have not typically subjected researchers’ FOI requests to independent review, although this may be changing in the United Kingdom and Australia, reflective of what Haggerty calls ‘ethics creep’. Here we present four arguments for why FOI requests in the social sciences should not be subject to formal ethical review by ERBs. These four arguments are: existing, rigorous bureaucratic vetting; double jeopardy; infringement of citizenship rights; and unsuitable ethics paradigm. In the discussion, we reflect on the implications of our analysis for literature on ethical review and qualitative research, and for literature on FOI and government transparency.
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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 | 0.667 | 0.706 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.017 | 0.109 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".