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Record W2892525529 · doi:10.5539/ass.v14n10p66

Status of Political Reforms Toward Violence’s Against Women in the Middle East

2018· article· en· W2892525529 on OpenAlexvenueno aff
Abdulrahman Al-Fawwaz

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsnot available
Fundersnot available
KeywordsMiddle EastLegislaturePoliticsPolitical scienceInequalityPsychological interventionFace (sociological concept)Development economicsPolitical economyEconomic growthSociologyEconomicsPsychologyLawSocial science

Abstract

fetched live from OpenAlex

Women are considered as equal and essential part of the society, and have all the rights to live according to their will. However, in various countries, they are not given such chances; even their legislative positioning is also weak. The purpose of the study is to critically review the status of political reforms made towards violence against women in the Middle East. The paper tends to investigate that how women of Middle East are treated unequally and unfairly. The findings of the paper reveals that the status of political reforms towards violence against women in the Middle East is weak as the societies are male-dominated. Females are not given equal opportunity to live and their quality of life is poor because there is no such strong implementation of legislative policies. There is much need of policy implications so that the political reforms can be made towards providing equal and fair rights to females. Women due to poor implementation of policies face the violence; however, governmental interventions can help to overcome such inequality in the Middle East.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.002
Open science0.0000.001
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 head0.066
GPT teacher head0.348
Teacher spread0.281 · 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
Published2018
Admission routes1
Has abstractyes

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