Bibliographic record
Abstract
2012年5月，中国家居建材团购网站CityTogo（城市团购网）的创始人、CEO贾光先生在杭州总部办公室里与同事开会，讨论公司团队建设问题。会上，负责业务的同事又提出要大量招聘业务人员的想法，因为“人太少，对客户要求的反应速度就跟不上。” 但是，负责人力资源的同事则摇头否定：“做不到。我们招聘要求高，速度没法快。如果招不到合适的员工，不能代表公司、不能为客户真正创造价值，对业务长期发展更加不利。”… … 会议结束了，但贾光一直在思考这个问题：竞争激烈，扩张速度如果慢于竞争对手就会失去市场份额，CityTogo需要大量人才。人才已经成了快速扩张中的瓶颈。
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.073 | 0.006 |
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".