Bibliographic record
Abstract
This study attempts to delineate $2 when they use social media, shop online, and make electronic payments using WeChat Pay and Alipay. It is part of a book I am writing on perceptions of privacy and surveillance in China and is grounded in an inductive content analysis of 58 semi-structured in-depth interviews I conducted late 2019 in Beijing, Shanghai, and Chengdu. Privacy is written with two different words in Mandarin: $2 (a personal thing you do not wish to disclose in public akin to Western definitions) and $2 (hiding a shameful secret). Most of my interviewees used the latter meaning: $2 . Privacy, thus, was $2 , understood as $2 (moral face - e.g., purchases of personal medicine, underwear and sex-related products, or weapons) and $2 (social face - eg., financial information). Moreover, they perceived the need to hide shameful information $2 : parents and supervisors, or hackers who would disclose personal information, but less so an abstract entity such as the government. For instance, several interviewees felt they could “hide on Weibo” using a pseudonym, despite the real-name registration policy. These findings on privacy may shed slight on how Chinese citizens view the digitalization of surveillance through facial recognition monitoring and the building of the social credit system, and contribute to culture-sensitive surveillance research.
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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 | 0.002 |
| 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 | 0.001 |
| 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".