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Gender and its Relationship with the Development of Islam on Ay Island, Banda Neira

2025· article· en· W4411557200 on OpenAlexaboutno aff
Muhammad Aldi, Retisfa Khairanis

Bibliographic record

VenueDialogia · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsIslamGeographySociologyArchaeology

Abstract

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Abstract: This research aims to analyze the relationship between gender and the development of Islam on Ay Island, Banda Neira, from a socio-religious perspective. The main focus of this research is the role of men and women in religious life, Islamic education, and their involvement in socio-religious practices. This research uses a quantitative method with a correlational approach. Data were obtained through surveys, interviews, participatory observation, and document analysis of the history of Islamic development on Ay Island. The results show that there are differences in participation between men and women in various socio-religious aspects. In religious leadership, 85% of formal positions are still dominated by men, while women are more active in informal Islamic education such as pengajian and madrasah, with 72% of community-based activities managed by women. However, only 35% of women hold leadership positions in formal socio-religious organizations. In addition, 64% of women feel they have limited access to large-scale religious activities, although 78% of communities have shown increased acceptance of women's active role in socio-religious activities. The implications of this study show that although Islam on Ay Island provides space for women's participation, there are still gaps in access and formal leadership. Therefore, efforts are needed to increase women's involvement in wider religious activities through more inclusive policies and strengthening women's capacity in leadership. The results of this study contribute to the understanding of gender dynamics in coastal Muslim communities and provide insights for academics and policy makers in developing Islam-based gender empowerment strategies. 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Rashid, Amber Gul, and Zaheeruddin Asif. “Gender Inequality in the Public Sphere as Perceived by Muslim Female Graduate Students at a Pakistani Higher Education Institution–a Critical Grounded Theory Perspective.” Journal of Islamic Marketing 16, no. 2 (2025): 668–88. https://doi.org/10.1108/JIMA-11-2023-0355 Rhouni, Raja. “Fatema Mernissi, the Demon of Coloniality and Decolonial Exorcisms.” Moroccan Thought, 2025, 476. https://doi.org/10.1163/9789004519534_019 Rinaldi, Kailey, Monica Messer, Ardis Hanson, and Janet Chan. “Utilization of Backward Design in Health Professional Education: A Rapid Review.” Journal of Professional Nursing, 2025. https://doi.org/10.1016/j.profnurs.2025.02.004 Safeer, Aqsa Kiran, Atiqa Kanwal, and Hafsa Maria Adeel. “A Critical Exploration of Gender Dynamics in The Beauty of Your Face by Sahar Mustafah: Islamic Feminism Perspective.” The Critical Review of Social Sciences Studies 3, no. 1 (2025): 1575–84. https://doi.org/10.59075/ywa34a93 Suryadi, Nanda, Muhamad Albahi, Norman Gisatriadi, and Sulaiman Musa. “Shariah Governance, Reputation and Customer Loyalty at Islamic Banks.” INVEST: Jurnal Inovasi Bisnis Dan Akuntansi 6, no. 1 (2025): 1–11. https://doi.org/10.55583/invest.v6i1.1189 Uddin, Kazi Ashraf. “Conducting Transgender Research with Rohingya Hijra Participants: Reflections on Methodological and Ethical Considerations.” Development in Practice, 2025, 1–18. https://doi.org/10.1080/09614524.2025.2474045 Zutu, Juliana. “Understanding Gender-Based Violence Responses During Emergencies and Disasters in Solomon Islands,” 2025.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.040
GPT teacher head0.289
Teacher spread0.249 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueDialogiaSame topicAsian Studies and HistoryFrench-language works237,207