MétaCan
Menu
Back to cohort
Record W4408117234 · doi:10.1080/29933021.2025.2471826

“I’ve survived a lot of things that not everyone survives”: A digital photo elicitation study of the roles of social media in the lives of child welfare-involved sexual and gender diverse youth

2025· article· en· W4408117234 on OpenAlexafffund
Shelley L. Craig, Ashley S. Brooks, Rachael Pascoe, Egag Egag

Bibliographic record

VenueSexual and Gender Diversity in Social Services · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsWelfareSocial mediaPhoto elicitationPsychologySociologySocial psychologyInternet privacyDevelopmental psychologyComputer sciencePolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Sexual and gender diverse youth (SGDY) are overrepresented in child welfare and experience myriad stressors in care. Strengths-based research highlights that SGDY utilize diverse resources—including social media—to enhance resilience and wellbeing. However, little is known about the roles of social media on the wellbeing and care experiences of child welfare-involved SGDY. This study examines SGDY experiences via digital photo elicitation and reflexive thematic analysis. Three themes were created that describe how the participants demonstrate resilience through strategic and adaptive social media use: a) disclosing and withholding; b) persevering and honoring; and c) upholding and leading. Implications for service providers working with child welfare-involved SGDY 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)0.003
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
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 head0.061
GPT teacher head0.281
Teacher spread0.220 · 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 routes2
Has abstractyes

Explore more

Same venueSexual and Gender Diversity in Social ServicesSame topicChild Welfare and AdoptionFrench-language works237,207