Bibliographic record
Abstract
本案例主要介绍了碧桂园集团（简称“碧桂园”）以及创始人杨国强家族在教育慈善方面的实践与探索，通过公益事业践行“希望社会因我们的存在而变得更加美好”的信念。2002年，杨国强一次性捐赠2.65亿元用于创办国华纪念中学，这也是全国第一所纯慈善、全免费的中学。2012年，在了解到慈善性质高等教育的缺失后，杨国强推动建立了碧桂园职业学院，利用碧桂园的产业资源，致力于“产教融合”的培养模式。2013年，国强公益基金会成立，旨在以更专业的方式运营慈善项目，有效推进公益扶贫事业，并立下了“让国强公益基金会即使离开碧桂园也能得到长期的发展”这一独立性目标。 涉猎教育慈善至今，碧桂园与国强公益基金会已硕果累累，帮助了数万名贫困学子通过教育改变命运，并为社会及碧桂园源源不断地输送人才。然而教育慈善的项目也在运营中面临诸多挑战，如国华纪念中学就面临着招生生源受限和日益增长的经费压力等问题。因此，如何对国华纪念中学的长远发展进行规划就成为一项重要议题，其中一个重要的问题则是如何平衡其经济和社会效益，即是否应该保持杨国强创立的慈善初心，还是为了增强其经济效益，以适应国强公益基金的经济独立性目标？同时，碧桂园的教育事业板块博实乐集团以及碧桂园职业学院也提供了参照或对比目标，供国华纪念中学参考发展模式。
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.077 | 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; 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".