Critically feminizing family science: Using femme theory to generate novel approaches for the study of families and relationships
Bibliographic record
Abstract
Abstract How do values, beliefs, and assumptions about femininity shape relational experiences? To answer this question, we critically feminize family science by applying femme theory to the field. Through this analysis, we present some of the ways that femmephobia (i.e., the systematic devaluation and regulation of femininity across all bodies and identities) is established in childhood and perpetuated throughout various relational contexts across the life course. Specifically, we examine how femmephobia is socialized via families, systematically normalized and perpetuated throughout childhood, and how it shapes gender‐based violence risk, perpetration, and tactics. We demonstrate how femme theory illuminates the importance of disentangling the intersectional axes of gender, sexuality, and gender expression, thereby generating novel approaches for family and relationship science and interventions that promote systemic social change. Subordinating and regulating femininity affects all individuals, making its disruption of critical importance for the prevention of gender‐based violence and the promotion of healthy families and relationships.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.023 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".