I'm just a girl in the world (That's all you'll let me be): Exploring young women's perceptions of hypersexualization and infantilization within experiences of girlhood
Bibliographic record
Abstract
Despite the visibility of ‘girl trends’ on TikTok, little research explores how women interpret and engage with these cultural messages and how they link to broader experiences of hypersexualization and infantilization. While scholars have documented how young women in North America are caught between competing expectations being hypersexualized yet infantilized, how these contradictions shape their daily lives remains unclear. Social media trends add to this complexity, blending nostalgia with empowerment while subtly reinforcing limiting gender norms. This study examines how women in their 20s navigate these tensions through engaging with girlhood and ‘girl trends’ on TikTok. Using focus groups, it captures both lived experiences and digital performances of femininity, offering insight into how social media shapes self-perception. Findings reveal that bodily awareness is central to negotiating hypersexualization, with agency mediating experiences between empowerment and shame. Participants expressed exhaustion with societal expectations, critiquing ‘girl trends’ as both acts of resistance and mechanisms of consumer-driven conformity. Nostalgia for girlhood fostered among solidarity but was also heavily commodified. Additionally, “I'm just a girl” memes functioned as coping mechanisms yet risked reinforcing infantilizing gender tropes. By extending girlhood beyond childhood, this study highlights TikTok's role in shaping female identity, challenging the tendency to dismiss girlhood as frivolous, demonstrating how media trends act as both a site of empowerment and constraint. Centering the voices of women in their 20s, this research underscores the complexities of digital femininity, revealing how social media serves as both a tool for self-expression and a reflection of broader cultural contradictions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".