Fighting Hislam : an investigation into Australian and North American Muslim women fighting sexism within their own communities from a pro-faith perspective
Bibliographic record
Abstract
This research investigates how Muslim women in Australia and North America fight sexism within their own communities from a pro-faith perspective. It examines the stories of the women who engaged in such work, their motivations, and their path to fighting sexism, the support and criticism they received from both Muslims and non-Muslims, and the role faith played in their work. Little previous research has been done in this field. The majority of the accounts of Muslim women portray them as passive victims of, or willing accomplices in perpetuating, sexism. That the negative attitudes towards feminism in many Muslim communities are based on histories of colonisation and secularism adds an extra layer of complexity to understanding the topic. To develop a nuanced understanding of how Australian and North American Muslim women fight sexism within their own communities from a pro-faith perspective, this study is enhanced by interviews with 23 Australian, US and Canadian female theologians, activists, writers and bloggers who shared their beliefs and experiences of struggling against patriarchy against their co-religionists. The women in this study show how they reconfigure internal tensions into knowledge production, grapple with the Double Bind, and embody a Third Way, all of which leads to them ultimately creating a new component of third wave feminism in the West. The research offers a crucial new understanding of Muslim women in minority contexts, the religious legacy they utilise, the forces that shape them, and forces they shape.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".