Bibliographic record
Abstract
互联网领域中，在线教育市场发展的势头日渐高涨，相比于转型线上业务的传统教育机构，互联网公司更有可能颠覆传统教育模式。从游戏起步的欢聚时代公司（简称YY），对教育行业并无太多经验，然而YY 拥有全球最大的团队语音工具YY语音，这项技术领先行业平均水平两年，能为YY进入音乐、教育、电话会议等其他行业带来优势。创始人兼CEO李学凌认为，YY很有可能通过在线课堂模式降低学生学习成本，改变讲师与学校收入分配格局，从而在教育领域开辟一片蓝海。然而，在现有的平台化模式下，YY教育业务增长的速度缓慢，合作伙伴如培训机构对互联网工具并不熟悉；而如果YY教育变成内容出品方，又缺少管理教师与课程的经验。此外，YY教育平台目前还是免费模式，学员向教师直接付费，随着业务的不断发展，YY应该创造怎样的商业模式获得收入？“在线教育”这块看上去可口的蛋糕，究竟如何做大？
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.061 | 0.011 |
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".