Bibliographic record
Abstract
案例主要讨论二手电商平台闲鱼的发展。闲鱼成立于2014年，是阿里巴巴旗下子公司。案例描述了闲鱼三个阶段的发展情况：闲鱼创立起步时制定与众不同的“闲置交易社区”的战略，发展期深耕社区，建立对用户和产品同时驱动的商业模式，通过一系列商业行动，2017年闲鱼的市场渗透率接近80%，从二手闲置行业的后进者变为领先者。之后面对转转的竞争，闲鱼转型平台，在轻运营模式下大力拓展品类和边界保持了竞争优势。然而，在二手闲置行业增速放缓、竞争日益激烈、平台诚信被质疑等不利因素之下，闲鱼面临不少挑战。闲鱼负责人下一步应该怎么做，才能保持领先地位呢？
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.003 |
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".