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Social Support and LGBTQ+ Individuals and Communities

2021· reference-entry· en· W3197693112 on OpenAlexaff
Áine M. Humble

Bibliographic record

VenueOxford Research Encyclopedia of Communication · 2021
Typereference-entry
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsOperationalizationSocial supportSocial psychologyPsychologyTransgenderSexual minorityLesbianMinority stressStressorSexual orientationClinical psychology

Abstract

fetched live from OpenAlex

Abstract Social support is an important resource that can help reduce stressful situations or buffer the impact of stressful situations for LGBTQ+ individuals. Many definitions of social support exist, but researchers often focus on emotional, informational, or practical support provided to a person. Social support is communicated by people close to a person as well as through institutional practices and policies and in communities. General trends around the world show increasing support for sexual-minority individuals—and to a lesser extent gender-minority individuals—but there are many countries still hostile to LGBTQ+ individuals. A number of individual-level and country-level variables are related to positive attitudes toward LGBTQ+ individuals. Social support is operationalized in many ways in quantitative research on LGBTQ+ individuals, usually used as a predictor of health outcomes. Some quantitative measures look at general social support, whereas others study social support within particular settings, or very specific ways in which support is communicated. Measures of social support specific to LGBTQ+ populations have been developed, such as The Gay and Lesbian Acceptance and Support Index. Research also looks at support at the community level—the broader community (often referred to as community climate) as well as LGBTQ+ communities. Qualitative research is valuable for exploring what social support means to various groups and for understanding how different social identities interact with each other. Many factors influence expectations and experiences of social support; thus, research should be contextualized. Rather than studying LGBTQ+ as a group, subgroups can be studied, along with intersectional research. When this is carried out, unique findings can appear. For example, lesbians in adulthood can include ex-partners and ex-lovers in their social support networks, and Black lesbian parents describe complex ways in which they interact with their families and religious communities. Different life course changes such as same-sex marriage and LGBTQ+ parenting provide opportunities to explore if and how social support is communicated to LGBTQ+ individuals. Who support is received from is also a key area of interest—families of origin, chosen families, friends, work colleagues, LGBTQ+ communities and broader communities, and so on. Later-life circumstances of LGBTQ+ individuals need focus, as these individuals often have smaller social support networks due to lifetime discrimination and cumulative life course experiences. Political situations involving elevated anti-gay rhetoric are also relevant contexts in which to study how social support can ameliorate minority stress. Research is starting to look at social support in formal organizations, many of which have developed guidelines for developing inclusive environments for sexual- and gender-minority groups.

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)0.001
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.144
GPT teacher head0.461
Teacher spread0.317 · 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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Citations3
Published2021
Admission routes1
Has abstractyes

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