Open Access: A Giant Leap towards Bridging Health inequities/Acces Libre Aux Connaissances : Un Pas De Geant Vers le Comblement Des Inegalites En Matiere De sante/Acceso Libre: Un Paso De Gigante Para Resolver Las Inequidades Sanitarias
Notice bibliographique
Résumé
Introduction Health knowledge generated in the world's laboratories is passed down the information chain through publications, through its impact and application, its subsequent translation into appropriate contexts for different user communities, arriving finally with health workers and the general public, as the diagram of the knowledge cycle from the Canadian Institutes of Health Research has shown. (1) Studies have shown that access to published health research by the research communities in developing countries is no longer fit for purpose. (2) As has been well documented, rising costs of subscriptions and permission barriers imposed by publishers have barred access to the extent that local health research and health care have been damaged through lack of information. (3,4) For example, Yamey (5) tells of a physician in southern Africa who could not afford full access to journals but based a decision to alter a perinatal HIV prevention programme on one single abstract. The full text article would have shown that the findings were not relevant to the country's situation. With the advent of the internet there is little justification for continuing to create barriers to access. Richard Smith, as the former editor of the British Medical Journal, said, Most research is publicly funded, and when the internet appeared it made no sense for research funders to allow publishers to profit from restricting access to their research. (6) This is true not only for publicly funded research but for private health charities around the world. As the Open Access Policy of the Wellcome Trust states, We ... support unrestricted access to the published output of research as a fundamental part of its charitable mission and a public benefit to be encouraged wherever possible. (7) Science is a collaborative process and openness is fundamental to knowledge advancement. Nowhere has this been shown more clearly than by the 2003 outbreak of SARS (severe acute respiratory syndrome) during which, at the height of the epidemic, there was unprecedented openness and willingness to share critical research information, leading to the identification and the genetic mapping of the responsible coronavirus by 13 collaborating laboratories from 10 countries. (8) The recent release of essential H1N1 data published in several toll-access journals relevant to the H1N1 influenza pandemic points to the recognition that access to health research information is critical in the containment of infectious outbreaks. (9) It is difficult to see how the United Nations' Millennium Development Goals can be achieved without free international access to the world's publicly funded research findings or without collaborative initiatives. Goals 4 to 7 depend on the sharing of research findings for success, while Goal 8, which emphasizes the need for global partnerships for development, recognizes that sharing knowledge and capacity building establish the infrastructure for building future aid programmes. Any solution to the inequality of access to health-care information must be based on the development of an independent and sustainable national research base. Lessons in development aid from the past few decades clearly show that mechanisms that reinforce the dependency culture are no longer appropriate. (10,11) Solutions The United Nation's HINARI, AGORA and OARE programmes, whereby registered libraries or qualified institutions in countries with a Gross Domestic Product (GDP) of
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 | 0,054 | 0,132 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,007 | 0,025 |
| Communication savante | 0,037 | 0,058 |
| Science ouverte | 0,005 | 0,025 |
| Intégrité de la recherche | 0,018 | 0,017 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,093 | 0,019 |
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 ».