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Record W3003692501 · doi:10.1177/1476718x19898724

What did your child do today? Describing young children’s daily activities outside of school

2020· article· en· W3003692501 on OpenAlexaffabout
Kristen A. Archbell, Robert J. Coplan, Linda Rose‐Krasnor

Bibliographic record

VenueJournal of Early Childhood Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsBrock UniversityCarleton University
Fundersnot available
KeywordsPsychologyDevelopmental psychologyContext (archaeology)Child developmentScreen timeActivities of daily livingPhysical activityMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to describe the daily activities of Canadian children outside of school. Participants were parents of N = 189 children (90 boys, 99 girls) in grades 1 to 3. The What Your Child Did Today parental telephone interview protocol was developed as a daily log of both the type and social context of children’s activities. Among the results, children spent almost half of their waking time in unstructured activities (e.g. free play), compared to 14 percent of on-screen, and 6 percent in structured activities (e.g. sports). Children spent about two-thirds of their time in the company of family followed by peers (22%), and only 10 percent of time was spent alone. Some gender differences were also noted (e.g. boys engaged in more screen time) and parental education was related to time spent in structured activities. Results are discussed in terms of implications for children’s socio-emotional development.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.101
GPT teacher head0.351
Teacher spread0.250 · 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 designObservational
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

Citations14
Published2020
Admission routes2
Has abstractyes

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