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Record W2184581523 · doi:10.1037/e629932010-001

Bullying Among Prison Inmates in Pakistan: An Exploration of the Problem

2010· dataset· en· W2184581523 on OpenAlexaboutno aff
Muhammad Azam Tahir, Kostas Bairaktaris

Bibliographic record

VenuePsycEXTRA Dataset · 2010
Typedataset
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
Fundersnot available
KeywordsPrisonPsychologyCollectivismContext (archaeology)ChecklistScale (ratio)Clinical psychologySocial psychologyCriminologyIndividualismGeographyPolitical science

Abstract

fetched live from OpenAlex

The study attempted at redefining bullying, its nature, scope, and dimensions in cultural perspective of Pakistan. Direct and Indirect Prisoners Checklist (DIPC modified) © Ireland 1999 and Rehabilitation in Correctional Settings Attitude Scale (RICS) © Rice, 1970 were used in the study. Randomly selected (400) male and female prison inmates from all four Provinces’ major prisons of Pakistan participated in the study. Study was conducted in the cultural context of a collectivist society, like Pakistan (developing country), while the previous studies were carried out in individualistic societies, i.e., in the UK, USA, or Canada (developed countries). Reliability values for the DIPC and RICS subscales were calculated and found to be in acceptable range, except for the Proactive /Positive Behaviors. Thus, all sub scales except for Proactive/Positive Behaviors towards Other” were included in the main analyses. The results suggested that victims experienced physical, psychological, theft-related, and indirect bullying to similar degrees. However, psychological bullying was the most prevalent, while physical bullying the least. Both male and female prisoners reported that they were victimized by bullying more than they perpetrated bullying, with gender having no difference. Demographic variables and prisoner's self-reported

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)0.001
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: Dataset · Consensus signal: none
Teacher disagreement score0.153
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.359
Teacher spread0.319 · 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
GenreDataset

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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venuePsycEXTRA DatasetSame topicBullying, Victimization, and AggressionFrench-language works237,207