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Record W4281568104 · doi:10.1080/0966369x.2022.2069685

From mandarin to mendicant: violence and transgender bodies in urban Pakistan

2022· article· en· W4281568104 on OpenAlexfundno aff
Daanish Mustafa, Abdul Rehman, Komal Kumar Bollepogu Raja, Aisha Mughal

Bibliographic record

VenueGender Place & Culture · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsMandarin ChineseTransgenderGeographyGender studiesSociologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Transgender bodies very effectively undermine social norms of gender binaries. We use a case study of transgender people in the twin cities of Rawalpindi/Islamabad in Pakistan to understand how social violence, middle class morality and relations to the state are embodied in transgender bodies. While in pre-colonial times the transgender people in South Asia were mandarins of the empire, during colonial and post-colonial times they have been reduced to the role of mendicants. We find that the research participants’ notions of a transgender identity are contradictory, in that they draw upon the idea of a feminine soul in a male body, but simultaneously they also consider it a constant process of becoming through deed. In urban Pakistan, it is through violent encounters with transgender bodies that toxic masculinities are relationally enacted. We argue, however, that transgender bodies also hold an emancipatory promise to bodies imprisoned in toxic masculinity.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.007
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.001
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 head0.024
GPT teacher head0.305
Teacher spread0.281 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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