Open Infrastructure Matters: Supporting Scholar-Led and Community-Driven Services to Advance Open Access
Notice bibliographique
Résumé
See RECORDING (starts at 01:50:45). Twenty years ago, open access emerged out of a crisis within scholarly communications. Back then, it was about solving the issue of cost as a barrier to accessing scholarly content, due to the increasing concentration of commercial publishing. Today, another crisis is relying on open access to remove barriers to creating and consuming scholarship. This time, however, our sights are set on increasing public access as a means to solve a global pandemic. While open scholarship requires information to be freely available, it costs money to create and sustain high quality books and articles, discovery services that provide access to them, and software that enables their creation. We have seen this in discussions and developments surrounding open access business models, including article processing changes (APCs), open access funds, and “subscribe-to-open.” Where such infrastructures do not generate commercial profits, they require financial support from the communities they serve, including authors, publishers, libraries, funders, scholarly institutions and other stakeholders, to make open access a reality. As we set up national networks, mandates, and other initiatives to support and promote open access, we must not forget another critical element: open infrastructure. In the open access context, “infrastructure” -- the "structures and facilities" -- refers to the scholarly communication resources and services, including software, that we depend upon to enable the scientific and scholarly community to collect, store, organise, access, share, and assess research. Open infrastructure provides the foundation for keeping costs down and quality high, ensuring community-driven development. But who funds open infrastructure? And how do we create a sustainable future for the services that many of us have come to rely on? This 20 minute session will examine three open infrastructure case studies: OpenCitations, OAPEN/DOAB, and the Public Knowledge Project. These three initiatives are currently being promoted by the Global Sustainability Coalition for Open Science Services (SCOSS), a network of influential organisations committed to helping secure open access infrastructure well into the future. Our panel of services will explore how the current round of SCOSS-supported projects are ensuring a sustainable future for open access scholarly publishing, and will discuss the essential role that governments, libraries, publishers and others are playing - and need to play - in making this a reality. Following the growth of open access publishing, scholar-led and community-driven open infrastructure and innovations have supported and facilitated the vital (and now urgent) need for open knowledge. What does the next twenty years look like for these services? And how can we work together to ensure open access isn’t just a response to crises, but rather the “new normal”?
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 | 0,036 | 0,101 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,012 | 0,007 |
| Communication savante | 0,033 | 0,049 |
| Science ouverte | 0,007 | 0,057 |
| Intégrité de la recherche | 0,012 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,047 | 0,027 |
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 ».