Deliberate Absence: Mapping the Presence of Indian Transgender and Gender Diverse (TGD) Youth in Social and Medical Rights-Based Work Initiatives for the Community
Bibliographic record
Abstract
Background: Adolescence, the transitional phase between childhood and adulthood, involves significant biological, social, cognitive and emotional changes. In India, adolescents (10–18 years) form 21% of the population, increasing to 33% when including those aged 10–24 years, making India home to the world’s largest adolescent population. The concept of adolescence, unlike the biological process of puberty, is culturally determined and influenced by globalisation and changing societal values. Objectives: This article aims to (a) elucidate the barriers hindering transgender and gender diverse (TGD) youth in India from accessing gender affirmation, including familial rejection, constraining legal provisions and inadequate public health infrastructure; (b) underscore the impact of socio-cultural and political attitudes on health disparities faced by TGD youth, emphasising the need for comprehensive and individualised healthcare and socio-cultural support; (c) advocate for a socio-medical approach to address the unique challenges of Indian TGD youth, focusing on collaborative efforts among healthcare professionals, social institutions and policymakers; (d) propose strategies for improving access to early gender-affirmative care, including training healthcare providers, promoting comprehensive medical support and advocating for the rights of TGD youth. Methods: A blind review of literature was conducted using PUBMED/MEDLINE, Google Scholar, Web of Science, PsycINFO and SCOPUS with keywords such as ‘transgender youth’, ‘nonbinary and gender diverse youth’, ‘gender-affirming medical care in India’ and ‘youth mental health’. The search eventually included peer-reviewed publications, books, reviews, editorials, opinion pieces, feature stories and individual case reports. Articles were screened and thematically analysed to synthesise findings. Results: The review highlights significant barriers to gender-affirming care for TGD youth in India, including familial rejection, restrictive legal frameworks and inadequate public health infrastructure. Socio-cultural and political attitudes contribute to health disparities, necessitating comprehensive healthcare and socio-cultural support. Conclusions: Addressing the challenges faced by TGD youth in India requires a socio-medical approach, emphasising collaborative efforts among healthcare providers, social institutions and policymakers. Strategies for improvement include training healthcare providers, promoting comprehensive medical support and advocating for the rights of TGD youth to ensure early and effective gender-affirmative care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".