PLATFORM AS NEW “DADDY”: CHINA’S GENDERED WANGHONG ECONOMY AND PATRIARCHAL PLATFORMS BEHIND
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper provides an explorative analysis of gender as a critical dimension of the prospering wanghong economy in China with special attention devoted to the e-commerce wanghong value chains that are yet to be examined by scholars so far. Wanghong refers to a particular stream of vocational Chinese internet celebrities that have acquired their celebrity online and have acute incentives through various models to liquidate such online influence by transforming followers into consumers. While wanghong economy is often projected as a new platform economy that is by the women and for the women on diverse media outlets, my analysis highlights the structurally embedded gender hierarchy of this platform business ecosystem and the platform power increasingly associated with patriarchal order as exemplified by the updated meanings constructed around the Chinese term “baba” (daddy), which now is used to refer to platforms by wanghong and netizens. By combining the analysis of female participation at different levels of wanghong economy with the “platform-as-daddy” discourse prevalent on Douyin, one of the most popular social media platforms, this paper seeks to connect the industrial analysis of wanghong economy as one of the most prominent “platform economies” in contemporary China with its cultural dimensions. It accentuates the key roles of major Chinese platform companies as not only new critical intermediaries in perpetuating the ongoing patriarchal system between the state and users but also active participants that actively construct, and aggressively profit from, the gendered wanghong economy value chains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it