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Record W4386656730 · doi:10.1093/eurpub/ckab164.597

8.O. Workshop: Developmental assets and resilience in gender minority youth: Towards a balanced research agenda

2021· article· en· W4386656730 on OpenAlexaboutno aff

Bibliographic record

VenueEuropean Journal of Public Health · 2021
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLesbianSexual minorityMinority stressPsychological resilienceTransgenderStigma (botany)InequalityPsychologyGender studiesSocial connectednessSociologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Since the late 1990s, health inequalities among sexual and gender minority (SGM) youth have been increasingly recognised and investigated. However, most studies have been conducted in North America, while the research landscape in Europe is bleak. Gender minority (e.g. transgender, non-binary, genderqueer and genderfluid) youth receive even less attention than their sexual minority peers (e.g. those identifying as lesbian, gay and bisexual). A growing number of researchers recognise that the studies so far have concentrated on the disproportionate burden SGM youth face across various health outcomes. This maintains a discourse depicting SGM young people as ‘victims' and ‘at risk'. This individualistic approach is problematic because it often fails to consider macro-level determinants of these health inequalities, including societal attitudes towards SGM individuals; processes of structural stigma; lack of visibility and positive role models; and erasure of SGM identities. There is evidence that many SGM youth live happy and balanced lives and have developed resilience in face of adversities. There are developmental assets and positive features associated with being an SGM young person, for instance ‘coming out growth' and a sense of authenticity; support from family and peers; sense of belonging and connectedness to LGBTI+ communities; and civic engagement and community work. We argue that future research should consider these and other developmental assets and positive factors and embrace them in their design. This does not mean that risk factors or existing health inequalities and their determinants (e.g. structural stigma and minority stress) should be downplayed or minimised. A balanced approach is needed, which strives to also understand the empowering factors that contribute to SGM youth resilience, and developmental ‘assets' which help them to grow and flourish. This workshop will present work of key researchers in the area of gender minority youth research in Europe and North America, including findings from evidence synthesis, methodological developments and concrete evidence on developmental assets. The first presentation by Elena Vaughan et al. will showcase a two-phased landscape and knowledge gap study which synthesises European research with SGM youth. Concepcion Moreno-Maldonado et al. will present evidence on how community engagement among gender minority youth in Spain is associated with health-related quality of life. Ashley Taylor et al. will introduce findings from the Canadian Trans Youth Health Survey on the importance of having positive role models for gender minority young people. In the final presentation, Elizabeth M. Saewyc will showcase how gender minority youth were identified in the British Columbia Adolescent Health Survey. Following the presentations, we look forward to discussing the findings and future perspectives on health research with gender minority youth with attendees. Key messages Research on gender minority youth has largely concentrated on risk factors and maintained a ‘victim’ discourse, while developmental assets and sources of resilience receive less attention. Researchers from Europe and North America present evidence on the positive aspects of gender minority young people’s lives and argue for a more balanced perspective for future studies.

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)0.021
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0080.007
Open science0.0030.011
Research integrity0.0120.010
Insufficient payload (model declined to judge)0.0240.008

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 head0.384
GPT teacher head0.473
Teacher spread0.088 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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