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Record W2990473330 · doi:10.18357/ijcyfs104.1201919285

SEXUAL HARASSMENT OF SYRIAN FEMALE YOUTH IN JORDANIAN REFUGEE CAMPS

2019· article· en· W2990473330 on OpenAlexaffvenue
Mohammed Abdel Karim Al-Hourani, Abdel Baset Azzam, Addison Mott

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHarassmentRefugeePsychologySanctionsCriminologyEconomic JusticeSexual violenceSocial psychologyGender studiesPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

This study aimed at documenting the sexual harassment of Syrian female refugees in refugee camps in Jordan. A purposive sample of 187 Syrian female refugees in the Za’atari camp was selected. The results showed that the environment of the camp played an important role in motivating males to harass females owing to the weakness of the security measures and the lack of sanctions upon deviant behaviors. Our findings show that females were subjected to numerous forms of sexual harassment, including hearing sexual jokes and sexual expressions, and being subjected to suggestive looks, sexual letters, and unwanted touching. Additionally, our results revealed that participants responded to sexual harassment by keeping silent because they feared making their situation worse by provoking conflict within their families. This left the victims without protection or the chance to obtain justice.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.346
Teacher spread0.300 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

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