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Record W2765341840 · doi:10.1080/08824096.2017.1384920

Parental Monitoring of Children’s Television Viewing in a Sample of Peruvian Caregivers

2017· article· en· W2765341840 on OpenAlexfundno aff
Fernando Ruiz-Dodobara, Peter Busse

Bibliographic record

VenueCommunication Research Reports · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsPsychologySample (material)Developmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Parental monitoring of children’s television viewing is an important family practice that helps children understand the messages they find on advertisements and program content. Research points at different dimensions of monitoring, including parental co-viewing, rules about when and how much time children can watch television, and active parental mediation. The study describes different dimensions of parental monitoring in a sample of 303 caregivers of primary school children living in Lima. Main findings reveal that about a third of the sample engaged in parental monitoring never, rarely or sometimes, the education level of the caregiver was positively associated with limiting the time children can watch television, and that child’s age was negatively associated with the frequency of active mediation and limits on the content children may watch on TV. Further research is needed in order to understand the practice of parental monitoring across children’s age groups in the context of Peru.

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)0.003
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 score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.137
GPT teacher head0.441
Teacher spread0.304 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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