“Imperial solidarity”: do queer and trans Afghan Muslims need “saving”?
Bibliographic record
Abstract
In August 2021, immediately after the abrupt withdrawal of the United States (US) from Afghanistan and the return of the Taliban, “saving” Afghan women and queer and trans Afghans was highlighted as a global humanitarian responsibility, from Canada to the United Kingdom, Germany, Ireland, France and the US. Echoing Lila Abu-Lughod’s famous question “Do Muslim women need saving?,” in this article, I ask: do queer and trans Afghan Muslims need “saving”? Through an in-depth “de/colonial” ethnographic study with queer and trans Afghan Muslims in Afghanistan and the US, I develop the concept of “imperial solidarity,” which refers to “savior” regimes of Eurocentric, white, liberal, middle-class, and queer and trans unities and sympathies that establish certain forms of queer and trans ties across borders while serving the imperial project of “divide and rule,” invasion and withdrawal, Islamophobia and homophobia, and save and kill. I argue that imperial solidarity situates the West as morally superior and Islam as anti-queer and trans, which then contributes to an already rising Islamophobia. Another political implication of imperial solidarity with which this article engages is queer and trans Afghan Muslims’ troubled sense of (be)longing, both within Muslim communities and broader queer and trans communities.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".