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Record W2943742178 · doi:10.1177/1049732319843502

“I Never Saw a Future”: Childhood Trauma and Suicidality Among Sexual Minority Women

2019· article· en· W2943742178 on OpenAlexafffund
Genevieve Creighton, John L. Oliffe, Alex Broom, Emma Rossnagel, Olivier Ferlatte, Francine Darroch

Bibliographic record

VenueQualitative Health Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of British Columbia
FundersMovember CanadaVancouver Coastal Health Research InstituteUniversity of British ColumbiaMovember Foundation
KeywordsAbandonment (legal)Historical traumaQualitative researchPsychologyPsychological resilienceSexual abuseClinical psychologySuicide preventionPoison controlPsychotherapistMedicineSociologyPolitical science

Abstract

fetched live from OpenAlex

While a significant health concern for sexual minority women, there is little qualitative research investigating their experiences of childhood trauma and suicidality. In this study, we used photovoice methods and an intersectionality framework. Drawing on qualitative interviews, we inductively derived three themes (a) Traumatized and discredited, (b) Cascading marginality, estrangement, and suicidality, (c) Reconstruction and reclaiming resilience. In Traumatized and discredited, we describe the sense of abandonment flowing from childhood trauma heightened by a lack of protection and neglect on the part of parents/guardians. The lack of support to deal with childhood trauma and the layering effects of marginality characterizes the theme Cascading marginality, estrangement, and suicidality. In the third theme, we discuss strategies for reconstruction and reclaiming resilience as participants worked to overcome these challenging experiences. Our study findings offer guidance to suicide prevention counseling programs for sexual minority women and affirm actions to address health inequities.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.767
GPT teacher head0.734
Teacher spread0.033 · 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

Citations13
Published2019
Admission routes2
Has abstractyes

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