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Record W4225319374 · doi:10.1111/chso.12579

‘We can play tag with a stick’. Children's knowledge, experiences, feelings and creative thinking during the COVID‐19 pandemic

2022· article· en· W4225319374 on OpenAlexafffundabout
Nwakerendu Waboso, Laurel Donison, Rebecca Raby, Evan Harding, Lindsay C. Sheppard, Keely Grossman, Haley Myatt, Sara Black

Bibliographic record

VenueChildren & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsCarleton UniversityYork UniversityUniversity of TorontoBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsViewpointsFeelingPandemicReflexivityAgency (philosophy)Isolation (microbiology)Coronavirus disease 2019 (COVID-19)PsychologySocial psychologySociologySocial scienceMedicine

Abstract

fetched live from OpenAlex

Using a relational approach, we draw on repeated interviews with a group of 30 diverse children from Ontario to share and reflect on their knowledge, experiences and feelings early in the COVID-19 pandemic. Prioritising relational interdependence and relational agency, this paper illustrates our participants' embedded engagements with the pandemic and their contribution to the co-production of knowledge. We emphasise their thoughtful responses to the pandemic; their creative, self-reflexive strategies for managing a difficult time; and their advice to others. We thus prioritise children's viewpoints and emphasise their relational interconnections with others during a time that was marked by social isolation.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.278
Threshold uncertainty score0.552

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.015
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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

Citations11
Published2022
Admission routes3
Has abstractyes

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