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Record W4366772198 · doi:10.5539/jedp.v13n1p78

Preschoolers’ Recognition of the Transmission of the COVID-19 Virus: A Pilot Study

2023· article· en· W4366772198 on OpenAlexvenueno aff
Lakshmi Raman

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsSocial distanceAsymptomaticTransmission (telecommunications)Coronavirus disease 2019 (COVID-19)DistancingPsychologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Virus2019-20 coronavirus outbreakDevelopmental psychologyVirologyMedicineDisease

Abstract

fetched live from OpenAlex

The following two studies examined preschoolers’ recognition of the transmission of COVID and the cold virus. Study 1 examined preschoolers’ recognition of the impact of symptomatic and asymptomatic conditions without social distancing in the transmission of the COVID virus. Study 2 examined the role of social distancing in the transmission of the cold virus. Results of Study 1 indicated that preschoolers recognize the transmission of the COVID virus both in the symptomatic and asymptomatic conditions. Study 2 demonstrated that preschoolers take into account the proximity factor when assessing the probability of the transmission of the common cold. The results of both of these studies strongly support the theory that children have an autonomous theory of biology in the preschool years.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.146
GPT teacher head0.420
Teacher spread0.274 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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