Bibliographic record
Abstract
In the year 2004, college student Xia from certain Beijing Vocational College was sentenced to be put in jail for six months for intimidating and blackmailing the school leaders. Crimes committed by college students became the focus of the society once again. The present essay approaches from the aspects of family, school and society to analyze the causes behind the crimes committed by college students and discusses in particular how to effectively prevent and control such crimes. Key words: college student committing crimes, family education training and instruction system Resume: En 2004, un etudiant Xia d’une ecole professionnelle a ete condamne a six mois de prison pour avoir menace et fait chante un dirigeant de l’ecole. La culpabilite des etudiants attire de nouveau l’attention de la societe. Le present article essaie d’analyse, sur les plans de la famille, de l’ecole et de la societe, les raisons de la criminalite des etudiants et expose particulierement comment prevenir et controler la culpabilite des etudiants. Mots-cles: culpabilite des etudiants, education familiale et systeme d’orientation 摘要： 2004年，北京某科技職業學院在校學生夏某因涉嫌實施爆相威脅並勒索校領導被判六個月徒刑。大學生犯罪問題再次成為社會關注的焦點。本文擬就從家庭、學校、社會三個方面對大學生犯罪的原因進行分析，並著重論述了如何更有效預防和控制大學生犯罪。 關鍵詞：大學生犯罪；家庭教育培訓和指導體系
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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".