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The aim to sequence, catalog, and characterize the genomes of all of Earth’s eukaryotic biodiversity is the shared mission of many ongoing large-scale biodiversity genomics initiatives. Reference genomes of global flora and fauna have the potential to inform a broad range of major issues facing both biodiversity and humanity, such as the impact of climate change, the conservation of endangered species and ecosystems, public health crises, and the preservation and enhancement of ecosystem services. Biodiversity is dramatically declining: 28% of species being assessed by the IUCN are threatened with extinction, and recent reports suggest that a transformative change is needed to conserve and protect what remains. To provide a collective and global genomic response to the biodiversity crisis, many biodiversity genomics initiatives have come together, creating a network of networks under the Earth BioGenome Project. This network seeks to expedite the creation of an openly available, “public good” encyclopedia of high-quality eukaryotic reference genomes, in the hope that by advancing our basic understanding of nature, it can lead to the transformational scientific developments needed to conserve and protect global biodiversity. Key to completing this ambitious encyclopedia of reference genomes, is the ability to responsibly, ethically, legally, and equitably access and use samples from all of the eukaryotic species across the planet, including those that are under the custodianship of Indigenous Peoples and Local Communities. Here, the biodiversity genomics community is subject to the provisions codified in international, national, and local legislations and customary community norms, principles, and protocols. We propose a framework to support biodiversity genomic researchers, projects, and initiatives in building trustworthy and sustainable partnerships with communities, providing minimum recommendations on how to access, utilize, preserve, handle, share, analyze, and communicate samples, genomics data, and associated Traditional Knowledge obtained from, and in partnership with, Indigenous Peoples and Local Communities across the data-lifecycle. 

Teacher turnover in science and mathematics is a significant and consistent challenge for K-12 education in the U.S. This paper provides: (a) an investigation of the relationship between teacher retention and several social and motivational factors; and (b) a comparison of Master Teaching Fellows (MTF) and non-MTF teachers in terms of their retention and social and motivational factors. Teachers are classified into three retention categories: (a) stayers, (b) shifters, and (c) leavers. Social and motivational factors included teaching self-efficacy, diversity dispositions, leadership skills, principal autonomy support, teacher-school fit (adapted from person-organization fit literature), and social networks related to teaching and education. Study 1 included about 250 science and math teachers from the gulf coast region of Texas. Study 2 included 167 science and math teachers across the country. Teachers completed a survey in the summer and fall of 2021. For study 1, multinomial logistics regression analyses indicate: (a) leavers have significantly higher levels of self-efficacy; and (b) shifters have significantly higher levels of leadership skills and lower levels of teacher-school fit. The second study findings indicate: (a) MTFs’ teacher leadership network and teaching self-efficacy are significantly greater than that of non-MTFs’; and (b) MTFs significantly tend to shift to a leadership position than non-MTFs do. 

Teacher turnover i science and mathematics is a significant and consistent challenge for K-12 education in the U.S. This paper provides: (a) an investigation of the relationship between teacher retention and several social and motivational factors; and (b) a comparison of Master Teaching Fellows (MTF) and non-MTF teachers in terms of their retention and social and motivational factors. Teachers are classified into three retention categories: (a) stayers, (b) shifters, and (c) leavers. Social and motivational factors included teaching self-efficacy, diversity dispositions, leadership skills, principal autonomy support, teachers-school fit (adapted from person-organization fit literature), and social networks related to teaching and education. Study 1 included about 250 science and math teachers from the gulf coast region of Texas. Study 2 included 167 science and math teachers across the country. Teachers completed a survey in the summer and fall of 2021. For study 1, multinomial logistics regression analyses indicate: (a) leavers have significantly higher levels of self-efficacy; and (b) shifters have significantly higher levels of leadership skills and lower levels of teacher-school fit. The second study findings indicate: (a) MTFs' teacher leadership network and teaching self-efficacy are significantly greater than that of non-MTFs'; and (b) MTFs significantly tend to shift to a leadership position than non-MTFs do.