Religious faith and transgender identities: The Dear Abby project
Bibliographic record
Abstract
Religion and spirituality have been associated in many studies with an impact on mental and physical health. However, the relationship between religious faith and transgender identities is not well studied. To understand this relationship, the LGBT Committee of the Group for the Advancement of Psychiatry undertook a qualitative analysis. Participants in this study are a subset of a larger project investigating the role of religion and spirituality among all members of the LGBTQ community. The larger study invited input on LGBTQ identity and faith using an announcement posted by the “Dear Abby” column, published in hundreds of newspapers around the globe. Of the 86 participants in the study, eight responses were examined by participants who identified as transgender. Qualitative analysis of these survey results revealed the following themes: awareness of gender identity and development, mental health, God’s creation and spirit, fear of rejection, ambivalent acceptance, self-sacrifice for community, reconciliation with faith. Themes of both faith identity and gender identity were prevalent. Aspects of dual-identity development were painful and conflictual, but other aspects offered comfort, acceptance, and joy. When a participant’s family and community showed even partial acceptance of their transgender identity, greater resilience and integration resulted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".