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Record W2471062855 · doi:10.1080/1550428x.2016.1187104

Partner Violence in Transgender Communities: What Helping Professionals Need to Know

2016· article· en· W2471062855 on OpenAlexaff
Betty Jo Barrett, Daphne Vanessa Sheridan

Bibliographic record

VenueJournal of GLBT Family Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTransgenderDomestic violenceLesbianScholarshipPsychologyGender studiesCriminologySociologyPoison controlSuicide preventionPolitical scienceMedicineLaw

Abstract

fetched live from OpenAlex

In recent decades, there has been an increase in scholarly attention devoted to the study of intimate partner violence (IPV) within rainbow communities. While a growing body of scholarship now informs our understanding of the experiences of gay, lesbian, and bisexual men and women with IPV, comparatively less is known about IPV within transgender communities. Drawing on the published literature on transgender intimate relationships, this article seeks to provide practitioners with a foundational understanding of IPV in the lives of transgender people. Specifically, we will examine (a) methodological, political, and social barriers to the creation of knowledge about transgender IPV; (b) the familial and relationship contexts of IPV within transgender communities; (c) the prevalence of IPV experienced by transgender survivors; (d) the dynamics of IPV perpetrated against and/or by transgender persons; (e) the problematic use of the “trans panic” defense by perpetrators of IPV in legal contexts; and (f) recommendations for supporting transgender survivors of IPV in ways that are trans-inclusive and trans-positive.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.236
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.411
Teacher spread0.312 · 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 teacher head, 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

Citations37
Published2016
Admission routes1
Has abstractyes

Explore more

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