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Enregistrement W2944613641 · doi:10.1097/01.hj.0000559493.29061.35

Make Quality Hearing Health Information Available to All

2019· article· en· W2944613641 sur OpenAlexaboutno aff
Shelly Chadha

Notice bibliographique

RevueThe Hearing Journal · 2019
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueWikis in Education and Collaboration
Établissements canadiensnon disponible
Organismes subventionnairesLondon School of Economics and Political ScienceWorld Health Organization
Mots-clésHearing lossHealth carePsychological interventionThe InternetPopulationQuality (philosophy)GlobeInternet privacyMedicinePublic relationsPsychologyMedical educationNursingAudiologyComputer sciencePolitical scienceEnvironmental healthWorld Wide Web

Résumé

récupéré en direct d'OpenAlex

Over six percent of the world's population has disabling hearing loss.1 Across the globe, it can take years for those with hearing problems to seek care. Even when care is sought, the prescribed interventions are not often adopted.2 This issue has motivated the World Health Organization to coordinate World Hearing Day (WHD), an annual event that aims “to raise awareness on how to prevent deafness and hearing loss and promote ear and hearing care across the world.”3hearing health, World Hearing DayThe Centers for Disease Control and Prevention argues that “plain language makes it easier for everyone to understand and use health information,”4 emphasizing its commitment to making high-quality information freely accessible to the public.5 As health articles on Wikipedia are collectively read more than 150 million times per month,6 one approach the National Institute for Occupational Safety and Health is taking to communicate research findings involves improving health content on Wikipedia.7 That includes the adoption by university programs of the WikiEducation Foundation https://wikiedu.org/8 platform to train students in Wikipedia editing. Through this mechanism, students contribute evidence-based content to Wikipedia as a class assignment.9 This year, NIOSH proposed and developed the online event Wiki4WorldHearingDay2019 http://bit.ly/2DzSdD410 to facilitate the improvement of Wikipedia content related to hearing, hearing health services, hearing testing, and preventive and rehabilitative interventions. The platform provided guidance and allowed anyone with access to a computer and the internet to participate in the campaign. Several institutions joined by either promoting the event or contributing content to Wikipedia, including the National Center for Environmental Health https://www.cdc.gov/nceh/, the National Center on Birth Defects and Developmental Disabilities https://www.cdc.gov/ncbddd/index.html, the Hearing Center of Excellence https://hearing.health.mil/, the French National Research and Safety Institute for the Prevention of Occupational Accidents http://en.inrs.fr/, the International Society of Audiology https://www.isa-audiology.org/, the Acoustical Society of America https://acousticalsociety.org/, the American Academy of Audiology https://www.audiology.org/, and Hear in Cincinnati https://www.linkedin.com/company/hear-in-cincinnati. Participants from Cochrane, Cochrane Ear, Nose and Throat https://www.cochrane.org/, and university programs in the United States, Canada, United Kingdom, Brazil, and South Africa also contributed expert content, which led to content being added in English, Portuguese, French, Spanish, Italian, and Swedish. Through the Wikimedia outreach dashboard http://bit.ly/2KLLUmA,11 we were able to monitor the contributions and their reach with a great level of detail. Tracking data from the platform launch on Jan. 21, 2019, to March 31, 2019, showed that 74,000 words were contributed to 90 existing and seven new Wikipedia articles, and 21 images were donated to the open access repository WikiCommons. These pages received more than 2 million views (the 66 editors must be delighted to see this level of readership!). Crowdsourcing of expertise and knowledge is relevant for public health. The transparency of editorial processes and engagement on Wikipedia make it easier for experts to address any concerns they might have over participation. The heightened level of review of Wikipedia health articles is only possible due to the generous dedication of contributors who are health professionals and collaborative ventures, such as Wiki4WorldHearingDay2019, with scientific associations and agencies.12 We encourage organizations and institutions across the world to join current and future efforts.13 The breadth and accuracy of the Wikipedia coverage of the sciences vary widely. Awareness campaigns present unique opportunities to make hearing-related content one of the better developed domains within Wikipedia while providing quality information to the global audience in a place where they actually look for it. Thoughts on something you read here? Write to us at [email protected]

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,730
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,002

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.

Tête enseignante Opus0,088
Tête enseignante GPT0,408
Écart entre enseignants0,320 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2019
Routes d'admission1
Résumé présentoui

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