Bibliographic record
Abstract
Shahnaz Khan's study of Muslim female identity in Canada is a worthycontribution to the literature on Muslim experiences in the West. Sheexplores how women negotiate their identities in-between the polarizeddiscourses ofOrientalism and Islam by occupying a hybridized third space.This third space is not only the site of resistance to the dominant Islamicand Orientalist prescriptives of Muslim female identity, but a starting pointfor Muslim women to engage in individual and collective projects to remapand reconfigure their identities in a process of cultural, political, andeconomic empowerment. Khan argues that progressive politics by and forMuslim women are possible only from this hybridized location. Her studyelucidates this third space's dynamics by examining the dialectic betweenthe personal narratives of culturally diverse Canadian Muslim women andthe political space they inhabit.In her introduction, Khan locates herself as a Muslim feminist intellectualwho does not practice but is influenced by Islam, as well as Orientalist,multiculturalist, and feminist discourses. In order to move away fromessentialist notions of "Muslim," Khan clarifies that she uses the term toreveal the fluidity and diversity of expressions associated with beingMuslim, including its use in both a religious and non-religious context.In chapter 1, Khan draws on the work of various social theorists to rupture the notion of a homogenous, static, and authentic culture. She does thisby emphasizing cultural fluidity, permeability, and shifting boundaries.Resisting and challenging the former serves as the premise of what istermed the third space, whereby hybridized identities are constructed froma wide and even contending range of influences, such as eastern and westerncultural forces and religion. For Muslim women, Khan outlines how thethird space disavows colonial authority and forbids the reign of dominantnarratives of either Islam (which legitimates patriarchal authority throughsacred texts) or Orientalism (which represents Muslims as the pejorative"Other"). This third space allows Muslim women to negotiate, resist, andreinvent the forces informing their realities.In the next few chapters, the personal narratives of 14 Muslim womenelucidate how Muslim women negotiate their own identities as they confrontracism and lslamophobia in the broader community, and sexism and ...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 0.010 |
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".