I have thought long about the same issue and beyond. The triple (wiki, Hypothesis, donations) could be a working way to search for OER, form a social group processing them, and optionally support the creators.

I imagine that as follows: a person wants to learn about X. They can head to the wiki site about X and look into its Hypothesis annotations, where relevant OER with their preferred donation method can be linked. Also, study groups interested in the respective resource or topic can list virtual or live meetups there. The date of the meetups could be listed in a format that Hypothesis could search and display on a calendar.

Wiki is integral as it categorizes knowledge, is comprehensive, and strives to address biases. Hypothesis stitches websites together for the benefit of the site owners and the collective wisdom that emerges from the discussions. Donations support the creators so they can dedicate their time to creating high-quality resources.

Main inspirations:

Deschooling Society - Learning Webs

Building the Global Knowledge Graph

Schoolhouse calendar

Seaman, K. L., Christensen, A. P., Senn, K., Cooper, J., & Cassidy, B. S. (2022). Age Differences in the Social Associative Learning of Trust Information. PsyArXiv. https://doi.org/10.31234/osf.io/b38rd

https://www.openbookpublishers.com/

Jung, Y., Lee, Y. K., & Hahn, S. (2021). Web-scraping the Expression of Loneliness during COVID-19. PsyArXiv. https://doi.org/10.31234/osf.io/59gwk

Antico, L., & Corradi-Dell’Acqua, C. (2021). Far from the eyes, far from the heart. COVID-19 confinement dampened sensitivity to painful facial features. [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/ewvp7

Barrick, E., Thornton, M. A., & Tamir, D. (2020). Mask exposure during COVID-19 changes emotional face processing. PsyArXiv. https://doi.org/10.31234/osf.io/yjfg3

Kozlowski, Diego, Jennifer Dusdal, Jun Pang, and Andreas Zilian. ‘Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation’. ArXiv:2011.02887 [Physics], 5 November 2020. http://arxiv.org/abs/2011.02887.

Medeiros, Priscila de, Ana Carolina Medeiros, Jade Pisssamiglio Cysne Coimbra, Lucas Emmanuel Teixeira, Carlos José Salgado, José Aparecido da Silva, Norberto Cysne Coimbra, and Renato Leonardo de Freitas. ‘PHYSICAL, EMOTIONAL, AND SOCIAL PAIN DURING COVID-19 PANDEMIC-RELATED SOCIAL ISOLATION’. Preprint. PsyArXiv, 20 September 2020. https://doi.org/10.31234/osf.io/uvh7s.

Bhatia, S., Walasek, L., Slovic, P., & Kunreuther, H. (2020). The More Who Die, the Less We Care: Evidence from Natural Language Analysis of Online News Articles and Social Media Posts. Risk Analysis, risa.13582. https://doi.org/10.1111/risa.13582

Rosati, G., Domenech, L., Chazarreta, A., & Maguire, T. (2020). Capturing and analyzing social representations. A first application of Natural Language Processing techniques to reader’s comments in COVID-19 news. Argentina, 2020 [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/3pcdu

Leppanen, J., Tosunlar, L., Blackburn, R., Williams, S., Tchanturia, K., & Sedgewick, F. (2020, July 6). Critical incidents in anorexia nervosa.

Edgcumbe, D. (2020). PrePrint Version (Edgcumbe, 2020): The developmental trajectory of open-mindedness: from 18 to 87-years of age. [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/fnrmv

Rahmani P, Peruani F, Romanczuk P (2020) Flocking in complex environments—Attention trade-offs in collective information processing. PLoS Comput Biol 16(4): e1007697. https://doi.org/10.1371/journal.pcbi.1007697

Alam, F., Sajjad, H., Imran, M., & Ofli, F. (2020). Standardizing and Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing. ArXiv:2004.06774 [Cs]. http://arxiv.org/abs/2004.06774