An ethical analysis of the impacts of the COVID-19 pandemic on the health of children and adolescents
Bibliographic record
Abstract
ABSTRACT The COVID-19 pandemic has impacted the lives of children and adolescents around the world. Hence, this study aimed to examine how the pandemic has impacted children and adolescents in Brazil through an ethical analysis. An interpretive analysis of Brazilian research on child and adolescent health during the pandemic was conducted. Recognizing this ethical dimension is pivotal to shedding more light on how responses to crisis situations, such as the current situation of the COVID-19 pandemic, can be shaped and where the priorities for action are according to all interested parties, situating the child between these parts of interest. Our analysis highlighted both direct and indirect effects surrounding the decision-making processes for children in the COVID-19 pandemic reality. These decisional processes must sustain the child’s right to participation to ascertain that the action taken is in the child’s best interests. Nevertheless, the Brazilian reality has shown a structural exclusion of children’s voices in decisions affecting them, particularly concerning the effects of the pandemic on their lives. Further studies must be conducted to deepen the knowledge about children’s best interests and their participation in the actions planned during the pandemic.
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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 | 0.027 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".