Research Libraries: an Incubator for Science Communication, Public Engagement and Literacy Skills
Notice bibliographique
Résumé
Research libraries must play an increasingly important role in society. In an era where questionable and unreliable sources of information abound and quickly proliferate, libraries are more important than ever helping users navigate the tidal wave of information from social media, news sites and other resources and make sense of a complicated and polarized landscape. When science literacy skills, defined as the knowledge and understanding of scientific concepts required for personal decision making and participating in civic and cultural affairs, are combined with information literacy skills, one is empowered to critically interpret and verify science as presented in the media. Science festivals and science engagement events in conjunction with research libraries provide ideal opportunities to combine these two literacy skill sets. A case study will be presented of how the University of Toronto Library, Canada’s largest research library, integrated variegated literacies into science outreach events designed to engage with a diverse community. The public, in its various forms, attends science festivals to engage with scientific experts as well as participate in a range of scientific activities. Programming at science outreach events held within the library will be discussed in how it can serve as a catalyst for deeper learning about information creation, authority and dissemination. For example, students and members of the public took a deep dive into the construction and context of authority by participating in Wikipedia-edit-athons and fake news workshops. By bringing experts out from behind classroom “paywalls” via public lectures and human library events, students and citizens can informally converse and engage in debate with scholars. The backdrop for this case study is the annual Science Literacy Week (SLW) as well as the science communication programming which has stemmed from it. SLW began as a grassroots event in 2014 at the University of Toronto and has since grown and developed into an annual federally funded week-long celebration of science which includes over 800 events put on by over 200 partners in 100 cities across Canada. Many of the 44 libraries at the University of Toronto, including non-science libraries, participate in planning SLW public engagement activities. Since the theme of SLW is changed annually, libraries can capitalise on timely trends and issues such as the concept of post-truth and the notion of information literacy as a social practice. The success of SLW spawned a science engagement portfolio of events held throughout the year within the library. This case study will also discuss the challenges as well as the opportunities of situating a research library as a social space for public engagement. Libraries with their long history of providing democratic access to information provide a natural setting for contemporary public engagement, debate and science communication.
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 | 0,026 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,027 | 0,024 |
| Communication savante | 0,042 | 0,025 |
| Science ouverte | 0,004 | 0,044 |
| Intégrité de la recherche | 0,008 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,011 |
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 ».