The Alchemy of Domination, 2.0?1 A Response to Professor Kecia Ali
Bibliographic record
Abstract
In her critical essay, “The Omnipresent Male Scholar,”2 Professor Kecia Alisets out to call attention to what she sees as the hegemonic privileging ofthe male scholarly perspective and the need to replace this with an academiclandscape more reflective and accommodating of the experiences andscholarly vantage points of women. To this end, she profiles the works ofseveral (Muslim) men in Islamic Studies (myself included) and highlightsthe various ways in which they omit, overlook, undervalue, or dismiss thetopic of women or the scholarly views and interventions of female scholars.Her arguments are reiterated and expanded (this time without naming hertargets) in her Ismail R. al-Faruqi Memorial Lecture delivered at the 2017annual conference of the American Academy of Religion.3 The present essayaims to respond to Professor Ali’s assessment of my work, most specificallyIslam and the Blackamerican (and to a lesser extent, Islam and theProblem of Black Suffering) alongside some of the broader issues she raisesas part of her general critique. I will leave it to the other male scholars sheprofiles to respond to what she has to say about their work ...
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.028 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.022 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".