Bibliographic record
Abstract
自2005年8月创立以来，上海我要网络发展有限公司（又称“51.com”）一直专注于提供高质量的社交网络应用服务。2011年，51.com开始进军网络游戏行业，公司持续的投入收获了一些成绩，却始终未能进入该行业的前十名。面对未来的发展，51.com的创始人兼CEO庞升东先生相信机遇与挑战并存。一方面，游戏行业的竞争一直非常激烈，包括51.com在内的网络游戏公司普遍面临着人才流失的问题。另一方面，在中国网络游戏行业诞生了很多富有盈利能力的初创公司，尤其是在手机游戏市场。为了应对内外部的挑战，庞升东决定采用裂变式创业的模式。这个案例旨在引导学员讨论庞升东在企业内部实施裂变式创业的前因后果，以及这种战略的优势与劣势。
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.023 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.147 | 0.026 |
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".