Emergency Medicine and Climate Change: Our Role in Helping to Explain a Difficult Concept
Notice bibliographique
Résumé
This letter is written as a rebuttal to the editorial by D.C. Cone et al. titled “Emergency Medicine and Climate Change” that appeared in the August 2009 issue of Academic Emergency Medicine (AEM).1 I would suggest that this editorial did a major disservice to the spirit of academic emergency medicine. As a practicing emergency physician, I have, over the years, come to expect AEM to provide me with rigorously peer-reviewed articles. Unfortunately, the editorial appears to have ignored these high standards by giving the same credence to opinion pieces by nonexperts as that provided by expert panels. As critically thinking individuals, I would hope that we would be able to recognize good science from bad. The fact that between 1993 and 2003, peer-reviewed journals such as Science and Nature had published 928 articles on climate change, none of which refuted the claim that climate change was occurring and that human release of greenhouse gases was responsible, should give pause to the blanket acceptance of climate change deniers.2 I do not believe that there are this many articles supporting anything we believe in emergency medicine. The authors also should be the first to appreciate the time lags between experimental discovery and publication. To be specific, the “2007 Intergovernmental Panel on Climate Change (IPCC)” was a secondary publication that relied on previously published peer-reviewed articles. The science that led to those articles was observed years before. In addition, the 2007 IPCC publication was a consensus document. Again, the authors must realize that consensus statements tend to moderate toward the middle when there is a range of evidence (in this case, models). In fact, the recent release of the United Nations report, 2009 Climate Change Science Compendium, based on 400 peer-reviewed studies published since 2006, found that both the pace and the scale of climate change are accelerating, along with the confidence among researchers in their forecasts.3 The report also showed that while carbon dioxide emissions from fossil fuel burning grew by 1.1% annually from 1990 to 1999, this increased to 3.5% between 2002 to 2007. The conservative nature of the consensus models that came out of the IPCC 2007 report is immediately apparent. The fact that there is still controversy and debate on this topic is in some part thanks to a well-organized campaign akin to the one organized by the tobacco industry years ago. (One of the steps taken by tobacco was to create The Advancement of Sound Science Coalition [TASSC].) This was an organization whose objective was to appear as a credible source for reporters and to encourage the public to question, from the grassroots up, the validity of scientific studies. TASSC has now moved into the climate change arena. The other reason for controversy and debate is, I suspect, secondary to the fact that most of us (me included) do not want to change our lifestyle and are unwilling to apply the same rigor to this topic as we do in our professional lives. Finally, while I applaud Hess et al. on their article,4 I suspect that issues such as emergency medical services vehicle emissions will be a very small part of the problem in the future. Emergency physicians should be aware of reports being used by the military and intelligence communities, such as the 2007 “National Security and the Threat of Climate Change” document5 and the “Age of Consequences: The Foreign Policy and National Security Implications of Global Climate Change.”6 Taking “old” data from the 2007 IPCC report, these documents create political and strategic scenarios that include food shortages and waves of Central American refugees moving north as changing rainfall patterns cause droughts and crop failures in the southwestern United States and Central America. In summary, academic emergency physicians have the tools to distinguish good science from bad. We should recognize the extraneous factors trying to raise doubt around climate change where none should exist, and we should advocate for our patients’ and our families’ futures by helping to provide clarity on this important subject.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,028 | 0,131 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,024 |
| Communication savante | 0,016 | 0,038 |
| Science ouverte | 0,006 | 0,010 |
| Intégrité de la recherche | 0,035 | 0,080 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,005 |
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 source (Gemma direct ou Codex distillé), 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 ».