High risk yet invisible: conflicting narratives on social research involving children and young people, and the role of research ethics committees
Bibliographic record
Abstract
Universities have a special status in society because of the position they hold within their communities and their responsibilities for civic leadership. Consequently, there are increasing calls on universities to make their processes, teaching and finances more transparent to the general public in order to promote greater accountability. Guidance from the Association for Research Ethics Committees includes openness as one of the key principles for research ethics governance but little is known about whether universities are making information about these processes available to the public. Additionally, given the central importance of children and young people as stakeholders in education research, there is particular interest in what the available information would reveal about their inclusion in social research. A search of the websites of 33 social science research‐leading institutions in the UK found that only 20 (60%) had publicly accessible information about ethics review and governance. The available information was highly variable in terms of detail, format and procedures and not very easy to locate. Information about the involvement of children and young people in social research was even more limited and variable; tending to emphasise the ‘vulnerable’ status of children as participants and yet providing little or no information about how to effectively support children to provide informed consent. The article concludes with discussion of the potentially concerning impact of this on the involvement of children and young people in research and the need for universities to do more to generate, share and encourage greater innovation in this area.
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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 | 0.125 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.036 | 0.131 |
| Scholarly communication | 0.034 | 0.033 |
| Open science | 0.004 | 0.033 |
| Research integrity | 0.012 | 0.022 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".