Personal Objectives and the Impact of Internet Cafés in China
Bibliographic record
Abstract
China has the largest population of Internet caf é s in the world.Chinese users of caf é s are predominantly young males, but there are also mature users, females, and migrant workers.There are few exclusive Internet caf é users, as most users connect to the Internet from a variety of places, including caf é s, home, school, office, and mobile devices.Users engage in a variety of activities, the most common being chatting, gaming, and Internet surfing.The Chinese government has an aggressive Internet caf é policy that aims to protect minors, ensure a safe user environment, and curb Internet addiction and undesirable social behaviors, but it seems to be largely driven by misconceptions about the impact of Internet caf é s on users ' lives.The objective of this study is to understand the perceived value of Internet caf é use to users as individuals and to China as a society.We examine the objectives users pursue when they visit such venues and the extent to which they feel they have achieved their objectives.An understanding of user motives and perceived achievements is key to understanding the phenomenal growth in China ' s Internet caf é s and why China ' s restrictive policies have been difficult to enforce.We find that users ' objectives for using Internet caf é s are reasonable and common among young people.According to self-determination theory, they are the types of goals people pursue to satisfy psychological needs for autonomy, competence, and relatedness.In the coming years, Internet caf é s are bound to remain critical access venues, especially for rural communities and migrant workers.China is rapidly modernizing, but some of its current policies to limit if not prevent use of Internet caf é s are controlling and undermining of autonomous motivation and are bound to fail.They also threaten adaptive activities and motives (such as gaining new knowledge), the psychological needs of users, and, by implication, their psychological well-being.Given the difficulties experienced to date with controlling regulatory policies, we recommend that government consider alternative strategies that help advance the country ' s digital agenda and facilitate self-determination and psychological well-being.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".