花间堂：情怀客栈的商业蜕变 Blossom Hill: Metamorphosis of Inns with Nostalgic Sensation
Bibliographic record
Abstract
当张蓓在2010年春天开出花间堂第一家分店——丽江植梦院的时候，这家只有20间客房的小客栈所讲述的故事只是关乎情怀——对于中国式的幸福生活的憧憬梦想。几年过去，凭借独特的设计理念与酒店文化，花间堂迅速成长为国内精品度假酒店领域一块响亮的牌子，源自情怀的生意越做越大。 成立至今，花间堂完成了三件大事：截至2013年10月，基于植梦院模式，花间堂在大丽江地区陆续开出10家分店，成功完成云南的本地复制，实现了打造“丽江客栈第一品牌”的阶段性目标；2012年4月，周庄花间堂开业，成为异地复制的样板，花间堂在华东和西南地区的拓展就此启动，目前两地已建成和建设中的项目有10余个；2014年5月，花间堂第一个度假村落——西溪花间堂完工，从民宿扩大到村落的产品升级战略落地。 在此基础上，张蓓又为花间堂在前期积累的品牌价值与设计运营能力找到了更广的出口。2015年6月，花间堂首个管理输出项目——无锡阳山稼圃集建成。据张蓓估计，2017年花间堂管理输出项目的体量将相当于过去若干年自投自建项目的总和。用张蓓的话说，花间堂2009~2014年所做的事是“养品牌”“建模板”。民宿产品成型，村落产品成型，财务模型被验证，提供后台支撑的总部平台功能不断完善……这些是从0到1再到10的过程。接下来花间堂要做的是，实现从10到100的大步拓展。 http://www.ceibsreview.com/show/index/calssid/28/id/3377
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.030 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 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".