Bibliographic record
Abstract
本案例首先呈现了以战略和价值观为双主线的阿里巴巴发展史（1999年—2020年），通过对两条线以双螺旋结构的方式齐头并进的描述，展示战略和价值观之间的互生关系。战略和价值观有一定的依从度，各自又有自由度。价值观的确立（“立法”）是一个从战略实践中来、到战略实践中去的过程。 接着，本案例描述了阿里巴巴对价值观的运用，主要是作为日常行为的守则（“执法”）和作为纪律条例（“司法”）。在此过程中必然牵涉到制度、组织、KPI等方面，案例中对阿里在这些方面的特色做法做了交代，并通过一系列具体事件，观察到阿里在价值观事件执法中逐渐走向弹性的趋势，并结合阿里发展的阶段性特征对其中的原因做了阐释。 最后，本案例展现了阿里在价值观宣贯（“普法”）方面正在和即将面临的挑战：一是规模扩大带来的价值观稀释问题，二是多元化经营带来的价值观异化问题。解决问题的钥匙分藏在过去、现在和未来。
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 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.015 | 0.027 |
| Scholarly communication | 0.025 | 0.018 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".