Toxic Communication on TikTok: Sigma Masculinities and Gendered Disinformation
Bibliographic record
Abstract
A growing body of research highlights digital platforms like TikTok’s pivotal role in shaping meaning for their users, particularly regarding gender perceptions. With TikTok increasingly serving as a search engine for teens, understanding how opinions are formed necessitates examining online content and interactions. Our article focuses on the construction of masculinity and gender dynamics with sigma videos on TikTok, emphasizing the digital practices that foster toxic communication. We define toxic communication as the deliberate framing and intensification of gender relations through the lens of male control and domination, alongside the denigration, devaluation, or defamation of feminine and non-binary identities associated with hegemonic masculinity. Adopting a socio-technical approach, we utilize a digital qualitative method of immersive observation to collect and analyze videos, posts, hashtags, and gender-related content. Our findings reveal that sigma toxic communication manifests in a spectrum ranging from subtle humor to explicit violence. This diversity of content functions as a “ready-to-think” framework, potentially appealing to a wide range of men across varying tastes, ages, and attitudes toward gender while perpetuating narratives that reflect and reinforce entrenched patterns of male dominance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".