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Record W4390600421 · doi:10.5590/jerap.2023.13.1.27

The perspective of university students on the availability and effectiveness of cyberbullying prevention and response initiatives on campus: Virtual semi-structured interviews on resources, barriers, and solutions

2023· article· en· W4390600421 on OpenAlexaff
Molly-Gloria R. Patel, Anabel Quan‐Haase

Bibliographic record

VenueJournal of Educational Research and Practice · 2023
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsWestern University
Fundersnot available
KeywordsPerspective (graphical)Psychological interventionPsychologyIntervention (counseling)Medical educationVulnerability (computing)TabooPublic relationsSociologyMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Cyberbullying is a problem in educational settings, and much of the research has focused on the development of effective prevention and response initiatives. Because of the vulnerability of children, cyberbullying research and intervention programs have largely targeted elementary students. A growing body of research has shown that cyberbullying is not limited to elementary settings, but the problem is also prevalent in postsecondary institutions, with potentially severe negative consequences. Yet, there is a gap in research about interventions tailored to this life stage. To address this gap, we conducted virtual semistructured interviews through Zoom with 21 university students on the availability and the effectiveness of prevention and response initiatives on campus, existing barriers, and potential solutions. We found that university students were concerned about a lack of available initiatives, and they identified several barriers, including a lack of cyberbullying conversations occurring on campus, limited knowledge about the impacts of cyberbullying on university students, and stigmatization associated with cybervictimization, which made it difficult for students to openly talk about their experiences. To remedy these barriers, university students offered several solutions: increasing education for postsecondary students, faculty, staff, and support teams; conducting studies examining cyberbullying from the unique life stage perspective of young adulthood and employing an ecological point of view; and finally, creating age-appropriate cyberbullying resources, such as flyers, webpages, and anonymous reporting systems. A central theme across these solutions was the need for conversations around cyberbullying experiences at the postsecondary level, as students perceived that it was treated as a taboo topic.

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)0.008
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.006
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0020.003
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 head0.077
GPT teacher head0.439
Teacher spread0.362 · 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 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
Published2023
Admission routes1
Has abstractyes

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