When Injustice Gets Old: A Systematic Review of Trans Aging
Bibliographic record
Abstract
A lack of knowledge regarding the needs and experiences of trans and gender-nonconforming older adults contributes to and perpetuates the experiences of marginalization associated with being trans. Mitigating the conditions of marginalization—including those that are compounded by age—requires the production of trans aging knowledge. It was with the intent to produce such knowledge that this systematic review was undertaken. In so doing, five medical databases, eight social science databases, and two gray literature databases were searched. These included the following: CINAHL (1942–), Medline (1942–), Health Services/Technology Assessment Texts, Web of Science, EMBASE (1947–), Sociological Abstracts (1952), Social Services Abstracts (1806–), Gender Studies Database (1972–), LGBT Life with Full Text, Ageline (1978–), PsycINFO (1806–), Scopus, ERIC, The New York Academy of Medicine Grey Literature Report, and Dissertations & Theses: Full Text. A total of 436 titles and abstracts were independently reviewed. Of these, 106 full-text articles were retrieved; 34 met the inclusion criteria and were reviewed. The following themes were identified: 1. the methodological challenges associated with conducting research with trans and gender nonconforming older adults;2. violence and abuse among trans and gender nonconforming older adults;3. discriminatory policies and practices in health and mental health care;4. the lack of appropriate HIV/AIDS education, prevention, and treatment strategies for trans and gender nonconforming older adults;5. obstacles in education, employment, government systems, and housing; and6. the lack of adequate social support networks. Gaps in the literature, recommendations for future research, and implications for policy and practice were also identified.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".