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Record W7112289011

Decolonizing Queer Migration: Iranian Voices in Exile

2025· book· W7112289011 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typebook
Language
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsQueerPoetryIdentity (music)PersecutionSexual identityPostcolonialism (international relations)RefugeeNegotiation
DOInot available

Abstract

fetched live from OpenAlex

This book retheorises queer identity formation processes of queer Iranians who have left Iran to escape persecution or discrimination on grounds of sexual orientation, gender identity and expression, or sex characteristics (SOGIESC). The book contributes to postcolonial research on gender and sexuality, augments life histories of exile, explores trauma-based cultural politics, blends poetry with more traditional methods of social science analysis in a creative form of participatory research, and makes a nuanced contribution to emerging queer studies of migration, transnationalism and exile. In particular, the book explores the lived experiences of queer Iranians in exile, by enquiring: a) how migration from Iran to ‘the West’ affects the way queer Iranians in exile negotiate their sexual and gender identity; b) how some feel misrecognised, retraumatised, or silenced in that process, others are able to understand and articulate their identities in new ways, and most have both positive and negative experiences during their ‘journeys’; c) how queer Iranians in exile negotiate culturally specific categories such as ‘LGBTIQ+’ and how innovative/tactical/strategic they are in resisting processes of determination/subjugation. The book investigates the difficulties of cultural translation and the ways in which Iranian experiences are read through the prism of dominant Western signifiers. The book explores the experiences of queer Iranians in exile in three countries generally seen as being of transition, destination or resettlement, respectively Turkey, the UK and Canada, and relies on the analysis of 57 interviews and five poetry workshops, reflecting the strong artistic and folk traditions of poetry in Iran.

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)0.003
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.021
Scholarly communication0.0060.006
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.291
Teacher spread0.247 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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