Bibliographic record
Abstract
本案例描述了哔哩哔哩（又称“B站”）如何在强敌环伺的在线娱乐产业成功突围并取得蓬勃发展。中国人口红利犹存，在线娱乐产业（包括视频、手机游戏和直播）继续呈现规模大、速度快的发展态势。玛丽·米克尔发布的《2019年互联网趋势报告》显示，2018年，中国移动互联网用户数量达到了8.17亿人，同比上涨9%，移动数据使用量同比增长189%，高于2017年的162%的增幅。[ https://www.bondcap.com/report/itr19/] 出生于90年代末-20世纪初的“Z世代”已然成为数字时代的消费主力军。这些数字原住民便是B站瞄准的主要客户群。为捕获年轻人的芳心，B站开发并定制了一系列特色服务。对比爱奇艺（百度旗下）、腾讯视频（腾讯旗下）和优酷（阿里巴巴旗下）等视频和流媒体服务头部平台，B站凭借独有的注册答题考试和弹幕文化，以及对其特有生态系统的持续管理【尤其是内容创作者（UP主）激励方案）】，成功建立起一个极具黏性的在线社区。 然而，B站的高歌猛进有可能因为收入来源不稳定等风险遭遇“急刹车”。除这些风险外，B站最大的挑战仍然源自其对核心竞争力的认知及把控：是坚守做小众社区的初心，拒绝铺天盖地的广告；还是增加更多主流内容，以吸纳更多的用户、投资者和广告主？
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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.041 | 0.006 |
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".