Bibliographic record
Abstract
本案例描述了亲和源集团有限公司（简称：亲和源）如何通过解决中国传统养老方式的痛点问题而创造共享价值。亲和源的养老服务除照料外，更解决老人精神层面的需求，让老人通过利他或者被需要提升价值感。为此，亲和源首创了会员制“家”养老模式并运营了十余年, 拥有两个版本，其中1.0版的上海康桥老年公寓入住率达95%，2.0版的上海迎丰老年公寓入住率达90%。亲和源“家”养老模式旨在让老人在其中得到足够的自由和尊重，将老人变成价值共创和共享者。 就在奚志勇致力于打造3.0版模式时，亲和源的母公司宜华健康称其2019年未达到业绩承诺，要求奚志勇向宜华健康支付补偿款8169万元，并敦促亲和源集中资源去销售库存项目，但奚志勇认为应着力完善模式为老人创造更大价值。奚志勇能否忽视资本要求而继续打造其3.0版模式？亦或，他能找到一个既令股东满意又能为会员创造更大价值的行动方案？
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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; 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".