WorldUnion and North XinAo (B): Confidential Information of North XinAo Negotiation Members
Bibliographic record
Abstract
2009年9月,世联地产与收购对象北方信澳的谈判陷入僵局。总部位于深圳的世联地产是首家在国内上市的房地产综合服务供应商,其董事长陈劲松及其管理团队制定了通过收购扩张到异地市场的战略,而北方信澳是北方某省的最大房地产服务企业,其董事长柯信诚与总经理和副总经理持有所有股权,希望尽快将股权出售套现。对世联地产来说,收购信澳对其实施扩张战略具有重大意义。虽然双方在收购定价和收购股权比例上存在重大分歧,但都不想轻易放弃,希望重新回到谈判桌上。案例(A)从世联地产的角度,讲述了陈劲松及其管理团队在收购价格、收购比例、付款方式等方面的谈判原则,而案例(B)则从北方信澳的角度出发,讲述了它在出售价格、出售比例、付款方式、退出策略等方面的最理想谈判结果。本案例可用于MBA、EMBA、高层管理人员等项目的谈判课程。
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".