Children as innovators: harnessing the creative expertise of children to address practical and psychosocial challenges of the coronavirus disease 2019 (COVID-19) pandemic – COVISION study protocol
Bibliographic record
Abstract
Background: We are currently in a period of transition, from the pre-COVID-19 (coronavirus disease 2019) era and the initial reactive lockdowns, to now the ongoing living with and potentially the after COVID-19 period. Each country is at its own individual stage of this transition, but many have gone through a period of feeling adrift; disconnected from normal lives, habits and routines, finding oneself betwixt and between stages, similar to that of liminality. Children and young people have been particularly affected. Aim: To increase the understanding of home and community-based strategies that contribute to children and young people’s capacity to adjust to societal changes, both during and after pandemics. Moreover, to identify ways in which children’s actions contribute to the capacity of others to adjust to the changes arising from the pandemic. The potential for these activities to influence and contribute to broader social mobilisation will be examined and promoted. Research design: To achieve the aim of this study, a participatory health research approach will be taken. The overarching theoretical framework of the COVISION study is that of liminality. The study design includes four work packages: two syntheses of literature (a rapid realist review and scoping review) to gain an overview of the emerging international context of evidence of psychosocial mitigations and community resilience in pandemics, and more specifically COVID-19; qualitative exploration of children and young people’s perspective of COVID-19 via creative outlets and reflections; and participatory learning and action through co-production.
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 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 | 0.033 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.077 | 0.013 |
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".