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Record W2150416293 · doi:10.3386/w21631

Bullying among Adolescents: The Role of Cognitive and Non-Cognitive Skills

2015· report· en· W2150416293 on OpenAlexfundno aff
Miguel Sarzosa, Sergio Urzúa

Bibliographic record

VenueNational Bureau of Economic Research · 2015
Typereport
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
FundersNational Institutes of HealthGrand Challenges Canada
KeywordsCognitionPsychologyCognitive skillNon cognitiveDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Bullying is a behavioral phenomenon that has received increasing attention in recent times. This paper uses a structural model with latent skills and longitudinal information from Korean youths to identify the determinants and effects of bullying. We find that, unlike cognitive skills, non-cognitive skills significantly reduce the chances of being bullied during high school. We use the model to estimate average treatment effects of being bullied at age 15 on several outcomes measured at age 18. We show that bullying is very costly. It increases the probability of smoking as well as the likelihood of feeling sick, depressed, stressed and unsatisfied with life. It also reduces college enrollment and increases the dislike of school. We document that differences in non-cognitive and cognitive skill endowments palliate or exacerbate these consequences. Finally, we explore whether investing in non-cognitive skills could reduce the occurrence of bullying. Our findings indicate that the investment in skill development is key in any policy intended to fight the behavior.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.867
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.134
GPT teacher head0.471
Teacher spread0.337 · 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 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

Citations19
Published2015
Admission routes1
Has abstractyes

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