The Social Negotiations of “Girls Like Us”: What Text-Messaging Dyadic Interactions Reveal About the Lives of Queer, Lesbian, and Bisexual Girls Living in the United States
Bibliographic record
Abstract
While there is emerging literature addressing the gendered nature of digital communication between youth, research about the everyday communications, friendships, and social relations of LGBTQ+ youth remains sparse. This study explores how 14 to 18-year-old, cisgender lesbian, bisexual, and queer girls living in the United States come to understand themselves and others in dyadic text messaging conversations of girls who were previously unknown to each other. Using grounded theory, this secondary data analysis identified the pervasiveness of heteronormative frameworks in participants’ communications with each other. Findings indicate that both digitally-mediated expressions of selfhood and queer identity are dynamic processes significantly shaped by normative discourses and participants’ desire to connect. Drawing on and contributing to girlhood and youth studies, this research provides insight into how queer cisgender girls construct literacies of self, sexuality, and gender, and establish connection, and how they resist heteronormativity to validate their own and each other’s sexual identities.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".