The voices of children and young people during <scp>COVID</scp> ‐19: A critical review of methods
Bibliographic record
Abstract
AIM: Critically review research methods used to elicit children and young people's views and experiences in the first year of COVID-19, using an ethical and child rights lens. METHODS: A systematic search of peer-reviewed literature on children and young people's perspectives and experiences of COVID-19. LEGEND (Let Evidence Guide Every New Decision) tools were applied to assess the quality of included studies. The critical review methodology addressed four ethical parameters: (1) Duty of care; (2) Children and young people's consent; (3) Communication of findings; and (4) Reflexivity. RESULTS: Two phases of searches identified 8131 studies; 27 studies were included for final analysis, representing 43,877 children and young people's views. Most studies were from high-income countries. Three major themes emerged: (a) Whose voices are heard; (b) How are children and young people heard; and (c) How do researchers engage in reflexivity and ethical practice? Online surveys of children and young people from middle-class backgrounds dominated the research during COVID-19. Three studies actively involved children and young people in the research process; two documented a rights-based framework. There was limited attention paid to some ethical issues, particularly the lack of inclusion of children and young people in research processes. CONCLUSION: There are equity gaps in accessing the experiences of children and young people from disadvantaged settings. Most children and young people were not involved in shaping research methods by soliciting their voices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".