Exploring Ethical Issues in Youth Research: An Introduction
Bibliographic record
Abstract
This special issue is devoted to exploring some of the ethical dilemmas that confront youth researchers. Although scholars who conduct research with other social groups obviously have to engage with important ethical issues in their own work, there are a number of ethical issues that are often seen as specific to young people. As Heath et al. (2009) have argued, in general these relate to the contextual factors which differentiate youth research from other forms of social research. These can be identified as: the way in which the lives of many young people are structured by various age-related institutions and contexts and framed by age-related policies; the construction of youth as a critical period for development and transition, which often leads to widespread concern with the monitoring of young peoples lives; and the relative powerlessness of young people as a social group within the research process for reasons which are often specific to their life phase (Heath et al., 2009). The five articles that comprise this special issue cannot, inevitably, discuss all of the ethical dilemmas that may arise in youth research as a result of these contextual factors. When taken together, they do, however, cover a variety of geographical contexts and methodological approaches. The empirical research reported in the articles was conducted in Australia, Canada, the United States and three nations of the United Kingdom (UK) (England, Scotland and Wales), and covers the following research methods: online research, face-to-face interviews, telephone interviews, restudies, visual methods and ethnography. In the sections that follow, we briefly introduce the five articles. We then outline three of the key themes that emerge from the special issue articles. These not only address important issues in youth research but also articulate with wider debates about the nature of ethical practice across the social sciences more generally.
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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 | 0.017 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".