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Record W4408648122 · doi:10.3389/fgwh.2025.1477145

Challenges and prospects: women's education in contemporary Afghanistan

2025· article· en· W4408648122 on OpenAlexaff
Basir Ahmad Hasin, Mir Mohammad Ayoubi, Nasar Ahmad Shayan

Bibliographic record

VenueFrontiers in Global Women s Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Human Rights and Reproductive Law
Canadian institutionsWestern University
Fundersnot available
KeywordsAfghanPolitical scienceGovernment (linguistics)Economic growthInterpretation (philosophy)Scope (computer science)Human rightsIslamPublic administrationDevelopment economicsSociologyLawGeography

Abstract

fetched live from OpenAlex

Since the fall of the republic government in Afghanistan on August 15, 2021, the situation for women's education has regressed drastically. This article explores the multifaceted impact of Afghanistan's Current DeFacto government policies on women's educational opportunities. With a historical overview of women's rights in Afghanistan, this article delves into the current restrictions imposed by the regime, including the ban on women's higher education and the limited scope of semi-higher education. This highlights the significant challenges faced by Afghan women, such as cultural barriers, economic hardships, and restrictive policies on women's rights. The article also discusses potential solutions, including international pressure, infrastructure development, and cultural shifts towards a more inclusive interpretation of Islam. By examining these factors, this article aims to provide a nuanced understanding of the ongoing struggle for women's rights and education in Afghanistan while emphasizing the resilience of Afghan women and the crucial role of global advocacy in supporting their fight for equality.

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)0.003
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0200.015
Scholarly communication0.0080.005
Open science0.0010.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.021
GPT teacher head0.344
Teacher spread0.323 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

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