Healthcare professionals as gatekeepers in research involving refugee survivors of sexual torture: An examination of the ethical issues
Bibliographic record
Abstract
This paper examines the ethical issues that arise when healthcare providers act as gatekeepers to research involving vulnerable populations. Traumatised refugees serve as an example of this subset of research participants. Highlighting the particular vulnerabilities of this group, we argue that specific ethical considerations are required that go beyond the conventional research approaches. While gatekeeping responds to some of those vulnerabilities, it risks wronging through unwarranted paternalism. Instead, we will propose that a relational ethics of justice and care serves as a more appropriate framework for responding to the challenges of research involving traumatised refugees. Specifically, such a framework allows us to reflect more deeply on the role of the gatekeeper. In conclusion, we recommend that clinicians and researchers collaborate with survivors' advisory groups in the development of specific research ethical guidelines.
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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 | 0.215 | 0.210 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.048 |
| Scholarly communication | 0.024 | 0.015 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.002 | 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".