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Record W4280564450 · doi:10.1111/chso.12590

Hiding and seeking: Children's lived experiences during <scp>COVID</scp> ‐19

2022· article· en· W4280564450 on OpenAlexaff
Donna Koller, Maxime Grossi, Meta van den Heuvel, Peter Wong

Bibliographic record

VenueChildren & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsPublic Health OntarioUniversity of TorontoHospital for Sick ChildrenToronto Metropolitan University
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Lived experiencePublic healthQualitative research2019-20 coronavirus outbreakEarly childhood educationSocial worldsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)SociologyPsychologyDevelopmental psychologyMedicineNursingSocial scienceInfectious disease (medical specialty)VirologyDisease

Abstract

fetched live from OpenAlex

A qualitative study explored the perspectives and lived experiences of school-age children during COVID-19 using a child rights lens. Twenty children between the ages of 7 and 12 participated in open-ended, virtual interviews. Our hermeneutic analysis found children's right to play and education were severely compromised leaving children to navigate between two worlds: the adult world of public health restrictions and that of their childhood. Despite challenges and lost childhood opportunities, children emerged as competent social agents and responsible citizens. Planning for future pandemics should include policies and practices that balance public health needs with the protection of children's rights.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.011
Scholarly communication0.0050.004
Open science0.0020.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.025
GPT teacher head0.283
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2022
Admission routes1
Has abstractyes

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