Achieving postfeminist ideals: a study of Chinese female wanghongs and their self-framing on social media
Bibliographic record
Abstract
This study investigates how Chinese female wanghongs on Douyin self-frame their image and identity, and how interactions between wanghongs and their followers co-frame the image of contemporary female Internet celebrities. We discovered that the four dominant self-frames of wanghongs are beauty, talent, personality traits, and gender expression through a qualitative coding analysis of the selected 30 female wanghongs’ posts and media interview narratives, along with viewer comments. Besides, we found that the co-framing of influencers and fans as a collective strategy assists women in breaking the aesthetic framework of traditional patriarchal culture. Furthermore, when conflicts arise between framing actors like wanghongs, fans, media, and political parties, female wanghongs tend to respond with resistance or compromise. We argue that examining the identity framing process of female wanghongs on social media can reflect the dilemma that Chinese feminists face when attempting to highlight women’s accomplishments in multiple roles.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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".