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Record W4220720049 · doi:10.1177/01430343221081994

Prevalence and predictors of staff victimization of students in Kosovo

2022· article· en· W4220720049 on OpenAlexaboutno aff
Aliriza Arënliu, Rami Benbenishty, Kaltrina Kelmendi, Zamira Hyseni Duraku, Jon Konjufca, Ron Avi Astor

Bibliographic record

VenueSchool Psychology International · 2022
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPeer victimizationContext (archaeology)Quarter (Canadian coin)Test (biology)Suicide preventionClinical psychologyPoison controlSocial psychologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Student victimization by school staff members has important potential consequences for students’ academic achievement and physical and psychological outcomes. Several studies have shown that such victimization exists in multiple contexts and there is considerable variation in prevalence among contexts. This study examined the prevalence of student victimization in public schools by staff members and its relationships with other school-related factors in the context of Kosovo. The sample was designed to represent all students from Grades 6–9 in 13 of Kosovo's 38 municipalities. The sample consisted of 12,040 students from 100 schools, 49.2% of whom were female. They were equally divided between Grades 6 to 9. Overall, more than a quarter of the students reported that a staff member victimized them in the last month. The least prevalent victimization type was sexual—touched or tried to touch you in a sexual manner (2.3%). The most prevalent physical behavior was slapping (15.8%); 12.7% reported being offended or humiliated by a staff member and 8.3% indicated that a staff member cursed them. Boys were victimized significantly more than girls for all types of victimization. The strongest predictors of staff victimization of students were students’ involvement in peer-to-peer victimization and risky behaviors, which were correlated with school climate. Future research should examine each type of staff victimization of students (emotional, physical, sexual) separately and test comprehensive models that include multiple predictors, including contextual and school-level variables and staff characteristics.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.993

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)0.0080.000

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 head0.014
GPT teacher head0.342
Teacher spread0.328 · 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.

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

Citations6
Published2022
Admission routes1
Has abstractyes

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