Binary trans parenting in a cisheteronormative society
Bibliographic record
Abstract
Context: Being a binary trans parent confronts the subject with cisheteronormativity, gender essentialism and transphobia. How will these challenges affect the experience, exercise and practice of parenthood? To what extent can family cohesion, adaptability and communication be a resource to help trans parents overcome these challenges?Method: We conducted semi-structured interviews with fifteen binary trans parents. The interviews were analysed using reflective thematic analysis (Braun & Clarke, 2019). Family cohesion, adaptability and communication were assessed using the FACES-IV (Olson & Gorall, 2006).Results: The results show the influence of pregnancy on the gender affirmation of trans parents, the impact of challenges on the transmission of gender roles to children and the main factors in the negotiation of parental designation. Family cohesion appears as a resource. It promotes echoeic adjustment, normalizing flexibility and relational resilience. We modeled these processes building the RAPT model. Support from the coparent plays an important role in family rebound. Our results also show the importance of sensory interactions between the trans parent and the child, in the development of parental identity and in the children's adaptation to gender affirmation.Conclusion: This study highlights the need to address the challenges faced by trans binary parents. It offers recommendations for therapy and training for professionals to support them effectively.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".