Notice bibliographique
Résumé
For the past three years, I have written this column on green healthcare, but this will be my last one. My work now has moved on – or back, to be more precise – to focus on public health services, away from green healthcare. In this final column, I want to reflect on the progress we have made and the challenges ahead. When we began the Canadian Coalition for Green Health Care in 2000, the topic was very peripheral to healthcare providers. It came in part out of a concern by some environmental organizations (notably Great Lakes United, the Toronto Environmental Alliance and the Canadian Centre for Pollution Prevention) with the environmental impact of the healthcare system, and partly out of concern on the part of several health professional organizations (notably the Canadian Association of Physicians for the Environment, the Canadian College of Health Service Executives, the CMA and the CNA) and a few hospitals (notably Toronto’s Hospital for Sick Children and Cambridge Memorial Hospital) with both the practical benefits of “greening” the healthcare system and with the ethical duty of healthcare professionals to do no harm to people, and by extension to the environment within which people live. This, in turn, came in part from a concern with the health of the environment itself and the many species that live within it, and in part from a recognition that doing harm to the environment results in doing harm to people. At the outset, although a group of (mainly) national organizations helped establish the coalition, much of its work became focused in Ontario. In particular, the Ontario Hospital Association became a willing and enthusiastic partner (and more recently, a member) and this led to three of the key activities of the coalition at the OHA annual convention: The Green Lane in the exhibits area featuring environmentally responsible products and services, an annual educational presentation featuring high profile speakers (Bob Rae this year, Ontario’s Environment Commissioner before that) and the Green Health Care Awards, which recognize outstanding achievements in Ontario in the areas of energy efficiency, pollution prevention, individual leadership and overall leadership. In addition to this set of annual events, the coalition has maintained a website (www.greenhealthcare.ca) and developed some key resources – notably a 70-page resource on many different aspects of “greening” healthcare (Doing Less Harm) that was funded by the Office on Sustainable Development at Health Canada – and a checklist for building green hospitals. The membership has slowly expanded to include a number of hospitals (several of which have attained ISO 14001 certification) and has some members beyond Ontario, notably in Winnipeg, Edmonton and Vancouver. A firmer base has thus been established for the next, necessary phase of the development of the coalition and its expansion to become a truly national organization that will play a key role in the greening of the Canadian healthcare system and the attainment of its vision, which is that “Canada’s healthcare system operates in an environmentally responsible manner.” If this bold vision is to be achieved, there are a number of challenges that need to be addressed.
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 | 0,018 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,014 | 0,014 |
| Communication savante | 0,030 | 0,031 |
| Science ouverte | 0,004 | 0,013 |
| Intégrité de la recherche | 0,029 | 0,042 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,051 | 0,022 |
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 ».