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Record W3109481992 · doi:10.5539/res.v13n1p1

Watching of Scary TV Shows by Children and Youth, Identification With Characters, and Resulting Fears and Nightmares

2020· article· en· W3109481992 on OpenAlexvenueno aff
Gila Cohen Zilka, Chen Goldberg

Bibliographic record

VenueReview of European Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyIdentification (biology)DramaAction (physics)Social psychologyDevelopmental psychologyClinical psychologyVisual artsArt

Abstract

fetched live from OpenAlex

The identification of children and adolescents with characters from the television programs they watch is not limited to the time when they view the program. The connection with the characters continues across the use of various digital means and in various realms of the children’s lives. The purpose of the present study was to examine the connections between patterns of use of various media, the degree of identification with characters from the programs watched, and the fears and nightmares experienced by the children after watching these programs. This is a mixed-method study. Two hundred ninety-six Israeli children and adolescents participated in the study; 45 children and adolescents among those who completed questionnaires were interviewed. The data were collected in 2017-2018. The data revealed that negative identification with the show characters was higher among children than in adolescents. Positive identification with the characters was higher among viewers of scary programs, among those who suffered from nightmares and fears, and among those who perceived the characters and plot as realistic. It was found that interest in programs involving tension, drama, and action increases the risk of nightmares and fears after watching these programs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

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

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 head0.064
GPT teacher head0.276
Teacher spread0.213 · 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 teacher head, 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

Citations1
Published2020
Admission routes1
Has abstractyes

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