Bibliographic record
Abstract
快速发展的中国网络视频行业正发生着巨变。2012年5月，中国网络视频用户覆盖率达到96%，用户规模首次超越搜索服务跃居第一，网络视频收视人群的行为日趋细分化。同年8月，位列行业前两位的优酷、土豆宣布合并，诞生了拥有视频用户覆盖率近80%的优酷土豆集团。对于这场行业“大地震”，集团董事长兼CEO古永锵认为，双方的战略合并将促进行业良性发展，降低内容采购成本、推动版权价格价值回归，优酷土豆合并后的规模效应将使领先优势更为明显，同时，双方后台的协同效应将提高整个平台的效率和价值。合并的优势显而易见，挑战亦不容小觑：优酷和土豆两个品牌高度相似，多品牌战略如何坚持？公司文化差异显著，组织结构如何优化？行业竞争愈加激烈，盈利模式如何改善？如何合中有分，统分为合，古永锵和他的团队交出的答卷对网络行业的并购整合具有相当的借鉴意义。
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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".