Bibliographic record
Abstract
Recently, the infection of AIDS becomes more and more serious in China, and brings about a far-reaching impact in Chinese society. In fact, AIDS has been an outstanding social problem. The public always discriminate against AIDS patients because most of them lack basic medical knowledge about AIDS. Chinese law can’t protect the AIDS patients’ legal rights and interests, so some patients commit some anti-society illegal action, including some serious crimes. In order to put an end to contagion of AIDS, China should amend and perfect pertinent legislation so that all the AIDS patients can live like common people in practice. Keywords: AIDS, Anti-discrimination law, Medical legislation, Medical ethic Resume Depuis les dernieres annees, le sida presente en Chine une tendance a la croissance rapide. La propagation du sida a produit des effets profonds sur la societe chinoise de sorte qu’il est deja devenu un probleme social saillant. A cause du manque de connaissances relatives au sida, le public a peur des patients porteurs de sida et les meprise. Le systeme juridique actuel de Chine ne suffit pas pour proteger leurs droits et interets legitimes, et cette situation les incite a commettre des actions antisociales, voire des crimes les plus graves.Contenir la propagation du sida demande des efforts communs de tous les sens, mais, il faut tout d’abord garantir les droits et interets legitimes des porteurs de sida pour leur permettre de vivre normalement dans la societe. Mots-cles: sida, legislation contre la discrimination, legislation medicale, morale medicale 摘 要 近來年，中國的艾滋病已經呈現了快速發展的態勢，中國的艾滋病情傳播給中國的社會造成了深刻的影響，已經成爲當前一個突出的社會問題。公衆由於對於艾滋病醫學知識的缺乏，對於艾滋病人産生不恰當的恐懼與歧視。中國目前的法律制度並不足以保護艾滋病人的正當權益，這又反過來使得艾滋病人産生一些反社會的行爲，甚至是嚴重的犯罪行爲。要從根源上遏制艾滋病的漫延勢頭，需要多方面的共同努力，但是，首先必須從法律上保障艾滋病人的合法權益，使其能夠像正常人一樣生活於社會。 關鍵詞：艾滋病；反歧視立法；醫療立法；醫學倫理
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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 | 0.023 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.044 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.013 | 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".