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Enregistrement W7017487033

Asian LGBT Non-Citizen Immigrants in California

2023· article· en· W7017487033 sur OpenAlexaboutno aff

Notice bibliographique

RevueeScholarship (California Digital Library) · 2023
Typearticle
Langueen
DomainePsychology
ThématiqueLGBTQ Health, Identity, and Policy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImmigrationSocioeconomic statusPovertyStressorStigma (botany)Minority stressEthnic groupPublic healthVietnamese
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This study used data gathered between 2015 and 2021 on the annual California Health Interview Survey to examine the demographic, socioeconomic, and health characteristics of Asian non-citizenLGBT immigrants.We focus on non-citizens 1 because they are a group at heightened vulnerability to low socioeconomic status and poor health.Information about U.S.-born Asian LGBT people and Asian non-LGBT non-citizens is presented to identify similarities and differences in the needs of these overlapping communities.Overall, Asian LGBT non-citizens were younger and less likely to be married or raising children than their non-LGBT counterparts.However, they reported higher levels of English proficiency.Almost a third of Asian LGBT non-citizens were living at less than 200% of the federal poverty level, and over a third reported not having a usual source of health care.For those with low incomes, half reported food insecurity. KEY FINDINGS• More than half of Asian LGBT non-citizens, cisgender and transgender, identified as bisexual (58.2%) and 28.4% as gay/lesbian, while some (13.4%)identified as heterosexual and were also transgender.• Among non-citizens, Asian LGBT people were younger than their non-LGBT counterparts. About two-thirds (67.7%) of AsianLGBT non-citizens were under the age of 35 compared to just over 40 percent (43.9%) of their non-LGBT counterparts.• Slightly more than half (52.0%) of all Asian LGBT non-citizens were cisgender women, about one-third (32.7%) were cisgender men, and 15.3% were transgender (of all gender identities and both sexes assigned at birth).• Among non-citizens, Asian LGBT people were less likely to be coupled and raising children than their non-LGBT counterparts.More than a quarter (28.0%) of LGBT non-citizens were married or living with a partner compared to 67.9% of their non-LGBT peers.About 7.4% ofLGBT non-citizens had kids compared to 37.8% of their non-LGBT peers.• Many Asian LGBT non-citizens are multi-lingual.Slightly more than half (51.8%) spoke one or more Asian languages at home, including Cantonese, Tagalog, Korean, and Vietnamese in addition to English.Another 26.5% spoke only languages other than English at home.Most (88.7%)LGBT non-citizens indicated they spoke English well or very well.However, more than one in ten (11.3%) reported not speaking English well.• Although most (85.5%)Asian LGBT non-citizens were in the workforce, almost a third (31.0%) were living at less than 200% of the federal poverty level.1 Non-citizens include those who do not have authorization ("documentation") from the U.S. government to be in the country, as well as those "authorized" to be in the U.S., including people who have a Permanent Resident Card ("Green Card"), work or student visas, and those seeking or who have received asylee or refugee status from U.S. Citizenship and Immigration Services. Asian LGBT Non-Citizen Immigrants in California | 3• While half (50.3%) of Asian LGBT non-citizens living at less than 200% of the federal poverty level were food insecure, relatively few (17.9%) were enrolled in the CalFresh food stamp benefits program.• More Asian LGBT non-citizens were experiencing psychological distress than their non-LGBT non-citizen peers (26.8% vs. 4.6%, respectively).• Over a third (38.8%) of LGBT non-citizens reported that they did not have a usual source of health care-more than twice the proportion of U.S.-born LGBT peers who said that they did not have a usual source of care (14.6%).These findings indicate a need to address the socioeconomic and health challenges faced by AsianLGBT non-citizens, including poverty, food insecurity, barriers accessing health care, and higher rates of psychological distress.The findings also indicate a need to increase enrollment in primary

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,480
Score d'incertitude au seuil0,954

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0030,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0120,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,285
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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