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Record W4392916927 · doi:10.1080/15564886.2024.2329107

Disclosure Decisions and Help-Seeking Experiences Amongst Victim-Survivors of Non-Consensual Intimate Image Distribution

2024· article· en· W4392916927 on OpenAlexfundno aff
Georgina Mclocklin, Blerina Këllezi, Clifford Stevenson, Jennifer Mackay

Bibliographic record

VenueVictims & Offenders · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsPsychologyDistribution (mathematics)Human factors and ergonomicsSocial psychologySuicide preventionPoison controlCriminologyClinical psychologyMedical emergencyMedicine

Abstract

fetched live from OpenAlex

The non-consensual dissemination of intimate images (NCII) is a form of technology-facilitated, image-based sexual abuse. Despite causing significant harm, research indicates a reluctance to seek support. Thus, this study aimed to develop practitioner recommendations for improving support accessibility by exploring NCII victim-survivors’ disclosure decisions and experiences of accessing support. Thematic Analysis of 31 UK adult victim-survivor interviews revealed informal support was favored, although some did not disclose to anyone. Disclosure responses ranged from supportive to judgmental. Barriers to help-seeking included stigma and perceiving formal support services as inaccessible. Recommendations for improving formal support accessibility such as service visibility, education and inclusive practices are discussed.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.306
Teacher spread0.286 · 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

Citations20
Published2024
Admission routes1
Has abstractyes

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