🌐 [translation-sync] [organization_capital.md] Update np.random → Generator API

[mmcky]

Automated Translation Sync

This PR contains automated translations from QuantEcon/lecture-python.myst.

Source PR

#1014 - [organization_capital.md] Update np.random → Generator API

Files Updated

• ✏️ lectures/organization_capital.md
• ✏️ .translate/state/organization_capital.md.yml

Details

• Source Language: en
• Target Language: zh-cn
• Model: claude-sonnet-5

---

This PR was created automatically by the translation action.

[netlify]

✅ Deploy Preview for astonishing-narwhal-a8fc64 ready!

Name	Link
🔨 Latest commit	3797433
🔍 Latest deploy log	https://app.netlify.com/projects/astonishing-narwhal-a8fc64/deploys/6a6d2d3845f11e00077a09e0
😎 Deploy Preview	https://deploy-preview-213--astonishing-narwhal-a8fc64.netlify.app
📱 Preview on mobile	Toggle QR Code... Use your smartphone camera to open QR code link.

---

To edit notification comments on pull requests, go to your Netlify project configuration.

[github-actions]

✅ Translation Quality Review

Verdict: PASS | Model: claude-sonnet-5 | Date: 2026-07-31
Routing: editor — 1 minor finding(s) in gating categories (accuracy/terminology/syntax/diff-check/other)

---

📝 Translation Quality

Criterion	Score
Accuracy	9/10
Fluency	9/10
Terminology	9/10
Formatting	10/10
Overall	9.2/10

Summary: The translation of the Bayesian learning section is accurate, fluent, and terminologically consistent. Mathematical formulas and equation labels are preserved intact, and the technical vocabulary aligns well with standard econometrics/statistics terminology in Chinese. Only very minor stylistic nitpicks were found; no substantive accuracy or formatting issues exist in this section. The Bayesian learning section accurately preserves all mathematical notation and equations without alteration Technical terms like 后验分布、后验均值、后验精度 are used consistently and correctly throughout the section The explanation of the signal model and posterior updating flows naturally in Chinese academic register

Suggestions:

• [minor · fluency] lectures/organization_capital.md — ### 贝叶斯学习 - '监督学徒的专家每期确定一个 $z$ 值': The phrase 'per period' (每期) is slightly ambiguous placement; while accurate, '每一期确定一个' would read more naturally in academic Chinese, but this is a very minor stylistic point. → 监督学徒的专家在每一期都会确定一个 $z$ 值
• [nit · terminology] lectures/organization_capital.md — ### 贝叶斯学习 - '因此，关于一个人的知识完全由这一对 $(m, h)$ 来刻画。': Minor stylistic choice: '这一对' is slightly informal compared to the more standard academic phrasing '该二元组' or '该对', but meaning is preserved correctly. → 因此，关于一个人的知识完全由二元组 $(m, h)$ 来刻画。

---

🔍 Diff Quality

Check	Status
Scope Correct	✅
Position Correct	❌
Structure Preserved	✅
Heading-map Correct	✅
Overall	7.5/10

Summary: The core code-cell translation fix (np.random.seed to default_rng) was correctly applied, but the target document also removed blank lines before many section headings that were not changed in the source, introducing unintended structural deviations.

Issues:

• Target document removed extra blank lines before numerous '##' headings (e.g., before 人员信息作为组织资本, 行业均衡, 综合效应, 关键性质, 团队信息, 企业专用人力资本, 转移组织资本的成本, 总结与启示) that were not changed in the source document, indicating unrelated/out-of-scope structural edits beyond the intended sync.
• The file diff stat (+3/-11) does not match a minimal 1-for-1 translation of the source's small code-cell-only change, confirming extraneous edits were introduced.

---

This review was generated automatically by action-translation review mode.

[Copilot]

Pull request overview

This automated translation-sync PR updates the Chinese organization_capital lecture to align with the upstream change that migrates legacy np.random usage to the NumPy Generator API, and refreshes the translation sync state metadata accordingly.

Changes:

• Replaced np.random.seed(...) / np.random.randn(...) usage with rng = np.random.default_rng(...) and rng.standard_normal(...) in an updated lecture code cell.
• Removed several whitespace-only blank lines in the markdown to normalize formatting.
• Updated .translate/state/organization_capital.md.yml metadata (source SHA, sync timestamp, model, mode, tool version).

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
lectures/organization_capital.md	Updates the lecture’s random number generation example to use the Generator API and cleans up whitespace-only blank lines.
.translate/state/organization_capital.md.yml	Updates translation-sync state metadata to reflect the new upstream source commit and tooling/model used.

---

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

[github-actions]

🚀 Deployed on https://6a6d340838aa1bf8d8741538--astonishing-narwhal-a8fc64.netlify.app