Notice bibliographique
Résumé
…In April 1997, a young Virginia man, intoxicated and driving 90 mph in a 35 mph zone, runs his car off the road and hits a tree. A female passenger, a high school senior, is killed. The Virginia newspaper reports it as a “terrible accident.” An account executive drinks too much alcohol, and gets behind the wheel of a car. On his way home, he kills a pedestrian. In his defense, he says, “It was an accident.” A man drives twice the posted speed limit because he's late for work. He loses control of his vehicle, which jumps the curb and kills five pedestrians in the blink of an eye. His attorney notes that accidents are a part of “everyday life.” What do these events have in common? They were all described as “accidents.” How can this be? An “accident” is defined as something unlucky that happens without being planned or intended or something that occurs by chance. While we are all horrified, no one is surprised that these tragedies occurred. They cannot be called chance or random. Changing the way we think and the language we use affects the way we behave and also the way we respond to these events. The word “accident” promotes the concept that these events are beyond human control. The fact is, motor vehicle crashes and the resulting injuries and deaths are predictable events. That they are predictable also makes them preventable. That is the key. It means we have the power to alter the course of these events.… We have so many highway deaths each year that they equal having a 737 jet crash every day. You can bet the American public would not tolerate a jetliner going down daily, yet somehow highway crashes and their costs have come to be viewed as the expected and uncontrollable consequences of everyday life. We have to change that. Through individual and group actions, some so simple as just changing the language we use, significant gains against this enormous societal problem can be made. Do You Want to Continue Receiving EMN? If this issue contains a business reply card on the front cover, we still need to hear from you! Please return the card today to ensure uninterrupted delivery. The American Board of Emergency Medicine was recognized by the American Board of Medical Specialties and the American Medical Association as the 23rd medical specialty member board in September 1979, when it held the first examination to evaluate physicians who sought certification in emergency medicine. By the end of 2001, ABEM had certified 18,553 physicians. ABEM can be reached at 3000 Coolidge Rd., East Lansing, MI 48823–6319; (517)332–4800, http://abem.org, or at [email protected]. The American College of Osteopathic Emergency Physicians supports quality emergency medical care, and promotes the interests of osteopathic emergency physicians and education. Founded in 1975, ACOEP since has worked to establish and accredit training programs in emergency medicine. Acting as part of the AOA Council on Postdoctoral Training, the ACOEP currently accredits programs in emergency medicine, a fellowship in emergency medical services, and jointly accredits programs in emergency medicine/family practice, emergency medicine/pediatrics and emergency medicine/internal medicine. For more information, contact ACOEP at 142 East Ontario St., Suite 550, Chicago, IL 60611; (312)587–3709; (312)587–9951 (fax); http://acoep.org. The Emergency Nurses Association serves the emergency nursing profession through research, publications, professional development, and injury prevention. Since its creation in 1970, ENA has worked on defining standards of excellence for emergency nursing and promoted quality emergency care through continuing education activities. Contact the Emergency Nurses Association at 915 Lee St., Des Plaines, IL 60016–6569; (800)900–9659, http://ena.org.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».