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Record W3154166822 · doi:10.1089/trgh.2020.0131

The Impact of COVID-19 on Economic Well-Being and Health Outcomes Among Transgender Women in India

2021· article· en· W3154166822 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTransgender Health · 2021
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransgenderGovernment (linguistics)Sex workCoronavirus disease 2019 (COVID-19)PandemicPolitical scienceTransgender womenBusinessEconomic growthPsychologySociologyGender studiesHuman immunodeficiency virus (HIV)MedicineEconomicsDiseaseSyphilisFamily medicineMen who have sex with men

Abstract

fetched live from OpenAlex

Coronavirus disease 2019 (COVID-19)-related lockdowns in India have disrupted the meager sources of income of many transgender women, including those in the hijra subculture who largely rely on money from providing blessings, begging, and sex work. Many have expended savings and taken high-interest loans, contributing to psychological distress. For hijras engaged in sex work, challenges to negotiating condom use and adhering to COVID-19 protective measures increase risks for contracting HIV and COVID-19 amid decreased access to HIV services. Many transgender women face challenges accessing COVID-19-related government welfare programs as they lack legal gender identity documents. Multisectoral and transgender-competent approaches are needed to mitigate the impact of the pandemic.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.439
Teacher spread0.370 · 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