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Record W3093593026 · doi:10.2196/20547

QueerVIEW: Protocol for a Technology-Mediated Qualitative Photo Elicitation Study With Sexual and Gender Minority Youth in Ontario, Canada

2020· article· en· W3093593026 on OpenAlexafffundvenueabout
Shelley L. Craig, Andrew D. Eaton, Rachael Pascoe, Egag Egag, Lauren B. McInroy, Lin Fang, Ashley Austin, Michael P. Dentato

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Toronto
KeywordsPhoto elicitationTransgenderIntersectionalityInterviewData collectionGrounded theorySocial mediaPsychologyOnline identityQualitative researchApplied psychologySocial psychologySociologyMedical educationComputer scienceGender studiesWorld Wide WebMedicineThe InternetKnowledge management

Abstract

fetched live from OpenAlex

BACKGROUND: The experiences of resilience and intersectionality in the lives of contemporary sexual and gender minority youth (SGMY) are important to explore. SGMY face unique experiences of discrimination in both online and offline environments, yet simultaneously build community and seek support in innovative ways. SGMY who identify as transgender, trans, or gender nonconforming and have experiences with child welfare, homelessness, or immigration have been particularly understudied. A qualitative exploration that leverages technology may derive new understanding of the negotiations of risk, resilience, and identity intersections that impact the well-being of vulnerable SGMY. OBJECTIVE: The objectives of the QueerVIEW study were to (1) enhance understanding of SGMY identities, both online and offline, (2) identify experiences of intersectionality among culturally, regionally, and racially diverse SGMY in Ontario, Canada, (3) explore online and offline sources of resilience for SGMY, and (4) develop and apply a virtual photo elicitation methodological approach. METHODS: This is the first study to pilot a completely virtual approach to a photo elicitation investigation with youth, including data collection, recruitment, interviewing, and analysis. Recruited through social media, SGMY completed a brief screening survey, submitted 10 to 15 digital photos, and then participated in an individual semistructured interview that focused on their photos and related life experiences. Online data collection methods were employed through encrypted online file transfer and secure online interviews. Data is being analyzed using a constructivist grounded theory approach, with six coders participating in structured online meetings that triangulated photo, video, and textual data. RESULTS: Data collection with 30 participants has been completed and analyses are underway. SGMY expressed appreciation for the photo elicitation and online design of the study and many reported experiencing an emotional catharsis from participating in this process. It is anticipated that results will form a model of how participants work toward integrating their online and offline experiences and identities into developing a sense of themselves as resilient. CONCLUSIONS: This protocol presents an innovative, technology-enabled qualitative study that completely digitized a popular arts-based methodology-photo elicitation-that has potential utility for contemporary research with marginalized populations. The research design and triangulated analyses can generate more nuanced conceptualizations of SGMY identities and resilience than more traditional approaches. Considerations for conducting online research may be useful for other qualitative research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/20547.

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)0.028
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.400
Threshold uncertainty score0.805

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.018
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0160.004
Scholarly communication0.0040.002
Open science0.0050.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1080.008

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 head0.514
GPT teacher head0.613
Teacher spread0.099 · 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
GenreProtocol

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

Citations16
Published2020
Admission routes4
Has abstractyes

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