The Structure of Knowledge Diffusion in Sciences and Consequences

The enterprise of modern science evolves alongside its underlying structure, encompassing interactions among scientists, institutions, and culture, as well as the development of scientific ideas and discoveries. The increasing availability of digitized scholarly data, coupled with enhanced computational power, offers unprecedented opportunities to characterize, critically examine, and untangle how these complex, intertwined entities shape the inner workings of science. Through three empirical studies, this dissertation investigates how underlying social and infrastructural elements can influence the production, diffusion, and consumption of scientific ideas and discoveries. The introduction outlines the three studies. The first chapter tackles the question of how tacitly encoded configurations and undocumented components can influence the estimates from randomized clinical trials, demonstrating the role of socio-epistemic bubbles in the production of scientific medical knowledge. The results suggest why meta-analyses may not mechanically resolve scientific disagreements and disputes, contrary to widespread expectations. The second chapter extends the analogy of bubbles to the realm of attention in biomedical scientific knowledge, reflecting the phenomenon of bubbles and collapses in financial asset markets. It reveals that restricted diffusion within social and scientific 'bubbles' can precede sudden collapses in scientific attention, offering a straightforward framework for identifying early signs of these bubbles in science. The third study explores how the presence of code repositories alongside machine learning research affects the citation rates of papers. It finds that the popularity of ML frameworks, such as PyTorch and TensorFlow, used in these repositories can have second-order network effects, underscoring the latent role of technological artifacts and infrastructure in scientific dissemination. The final chapter concludes the dissertation with reflections and outlines future research directions

Sete desastres relacionados à escola: Lições para legisladores e funcionários da escola

Students are highly dependent on the emergency planning and evacuation decisions made by policymakers and school personnel when disasters occur. The purpose of this study was to examine selected cases of school-related disasters, highlighting how factors of the school context intersected with natural hazards and subsequently affected schoolchildren. Purposeful maximal sampling was used to select school-related disaster cases for their geographical diversity, different instructional contexts, and types of initiating hazards. Among these, seven cases with broad considerations pertaining to educational policy and safe school environments were selected. A within-case analysis was conducted of each case, followed by a cross-case thematic analysis. Six overarching factors were found in the thematic synthesis of the findings. First, school safety practices apply anytime children are under the supervision of school personnel, making knowledge of emergency procedures across multiple types of school settings essential. Second, elements that place schoolchildren at risk also place school personnel at risk. Third, teachers and school administrators need to be well-trained and knowledgeable enough to make independent decisions in emergency situations. Fourth, children must know emergency procedures so they may take independent action, given teachers are also at-risk during disasters. Fifth, most school disasters can be prevented through safe school construction. Finally, it is the responsibility of policymakers to ensure schools are safe learning environments for children. By participating in and advocating for a culture of preparedness, educational policymakers can better protect schoolchildren, as well as school personnel, in disaster situations. Los estudiantes son muy dependientes en la planificación de emergencia y la evacuación de las decisiones tomadas por los políticos y la escuela cuando los desastres se producen. El propósito de este estudio fue examinar los casos de los problemas relacionados con la enfermedad y mostrar cómo los factores de la intersección del contexto intersectorial con las poblaciones naturales y la afectación de la escuela. En el caso de los niños, los niños y las niñas, Se han encontrado seis argumentos. En primer lugar, las normas de seguridad de la escuela aplican a los niños de edad bajo la supervisión de la escuela de trabajo, haciendo un seguimiento de los procedimientos de seguridad a través de varios tipos de la escuela de configuración esencial. En segundo lugar, los elementos que sitúan a los escolares en el riesgo también a la escuela en el riesgo. En tercer lugar, los maestros y los maestros de la escuela necesitan estar bien informados y bien informados para tener decisiones independientes en situaciones de emergencia. En el caso de los niños, los hijos deben saber los procedimientos de emergencia que pueden llevar a cabo la acción independiente, dado que los maestros también están en riesgo durante los desastres. La edad, la mayoría de los profesionales de la salud pueden prevenirse a través de la escuela de seguros. Por lo tanto, es la responsabilidad de los políticos para que las escuelas son seguros de aprendizaje de los hijos para los niños. Por la defensa de la cultura de la preparación, las políticas educativas pueden mejorar el cuidado de la escuela y la escuela en situaciones de desastres.Os estudantes são muito dependentes do planejamento de emergência e da evacuação de decisões tomadas por políticos e pela escola quando ocorrem desastres. O objetivo deste estudo foi examinar os casos dos problemas relacionados à doença e mostrar como os fatores de intersecção do contexto intersetorial com as populações naturais e a afetação da escola. No caso de crianças, meninos e meninas, seis argumentos foram encontrados. Em primeiro lugar, os padrões de segurança da escola aplicam-se a crianças mais velhas sob a supervisão da escola de trabalho, seguindo os procedimentos de segurança através de vários tipos de ambientes essenciais à escola. Em segundo lugar, os elementos que colocam as crianças em risco também na escola em risco. Em terceiro lugar, professores e professores precisam estar bem informados e bem informados para ter decisões independentes em situações de emergência. No caso de crianças, as crianças devem conhecer os procedimentos de emergência que podem realizar ações independentes, uma vez que os professores também estão em risco durante os desastres. Idade, a maioria dos profissionais de saúde pode ser evitada através da escola de seguros. Portanto, é responsabilidade dos políticos que as escolas estejam seguras para aprender crianças para crianças. Ao defender a cultura de preparação, as políticas educacionais podem melhorar o atendimento da escola e da escola em situações de desastre

The Sendai Framework for Disaster Risk Reduction and Persons with Disabilities

In this paper, the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) is evaluated with respect to its ramifications for persons with disabilities. In the SFDRR, persons with disabilities were referenced either directly or indirectly as part of the preamble, the guiding principles, the priorities for action, and the role of stakeholders. In addition, the 2015 World Conference on Disaster Risk Reduction, during which the SFDRR was adopted, incorporated explicit recommendations toward a disability-accessible and inclusive environment not evident in previous disaster risk reduction conferences. The infusion of disability-related terms and concepts such as accessibility, inclusion, and universal design throughout the SFDRR document was significant. These concepts, which have their origin in disability studies, are used in the SFDRR document to refer to the needs of all in disaster, not only to people with disabilities. These disability-related concepts will now serve the field of disaster risk reduction as important overarching disaster-related principles. The authors conclude that the SFDRR has firmly established people with disabilities and their advocacy organizations as legitimate stakeholders and actors in the design and implementation of international disaster risk reduction policies

Aligning Large Language Models through Synthetic Feedback

Aligning large language models (LLMs) to human values has become increasingly important as it enables sophisticated steering of LLMs, e.g., making them follow given instructions while keeping them less toxic. However, it requires a significant amount of human demonstrations and feedback. Recently, open-sourced models have attempted to replicate the alignment learning process by distilling data from already aligned LLMs like InstructGPT or ChatGPT. While this process reduces human efforts, constructing these datasets has a heavy dependency on the teacher models. In this work, we propose a novel framework for alignment learning with almost no human labor and no dependency on pre-aligned LLMs. First, we perform reward modeling (RM) with synthetic feedback by contrasting responses from vanilla LLMs with various sizes and prompts. Then, we use the RM for simulating high-quality demonstrations to train a supervised policy and for further optimizing the model with reinforcement learning. Our resulting model, Aligned Language Model with Synthetic Training dataset (ALMoST), outperforms open-sourced models, including Alpaca, Dolly, and OpenAssistant, which are trained on the outputs of InstructGPT or human-annotated instructions. Our 7B-sized model outperforms the 12-13B models in the A/B tests using GPT-4 as the judge with about 75% winning rate on average.Comment: Preprint, 9 pages (with 10 pages of supplementary

Effects of instructor’s coaching behavior in the military educational environment on self-directedness in learning of cadets at Korea Army Academy at Yeong-cheon (KAAY)

The purpose of this study is to test the effects of instructor’s coaching behavior in the military education and training on self-directedness and learning outcome of cadets. To this end, the self-report questionnaires was used to collected data from 409 cadets in the 4th grade of the KAAY in the six-week military education and training from July to August 2022. The collected data were analyzed using Structural Equation Modeling (SEM). The result revealed that the instructor’s coaching behavior had a significant effect on the self-directed learning of cadets and the learning outcomes of cadets. We also found self-directedness in the learning of cadets mediated the instructor’s coaching behavior and learning outcomes. The findings could help to pay attention to the instructor’s coaching behavior as a strategy to foster self-direction in the learning of cadets

Effects of instructor’s coaching behavior in the military educational environment on self-directedness in learning of cadets at Korea Army Academy at Yeong-cheon (KAAY)

The purpose of this study is to test the effects of instructor’s coaching behavior in the military education and training on self-directedness and learning outcome of cadets. To this end, the self-report questionnaires was used to collected data from 409 cadets in the 4th grade of the KAAY in the six-week military education and training from July to August 2022. The collected data were analyzed using Structural Equation Modeling (SEM). The result revealed that the instructor’s coaching behavior had a significant effect on the self-directed learning of cadets and the learning outcomes of cadets. We also found self-directedness in the learning of cadets mediated the instructor’s coaching behavior and learning outcomes. The findings could help to pay attention to the instructor’s coaching behavior as a strategy to foster self-direction in the learning of cadets

Prevalence and Risk Factors for Refractive Errors: Korean National Health and Nutrition Examination Survey 2008-2011

PURPOSE To examine the prevalence and risk factors of refractive errors in a representative Korean population aged 20 years old or older. METHODS A total of 23,392 people aged 20+ years were selected for the Korean National Health and Nutrition Survey 2008-2011, using stratified, multistage, clustered sampling. Refractive error was measured by autorefraction without cycloplegia, and interviews were performed regarding associated risk factors including gender, age, height, education level, parent's education level, economic status, light exposure time, and current smoking history. RESULTS Of 23,392 participants, refractive errors were examined in 22,562 persons, including 21,356 subjects with phakic eyes. The overall prevalences of myopia ( 0.5 D) were 48.1% (95% confidence interval [CI], 47.4-48.8), 4.0% (CI, 3.7-4.3), and 24.2% (CI, 23.6-24.8), respectively. The prevalence of myopia sharply decreased from 78.9% (CI, 77.4-80.4) in 20-29 year olds to 16.1% (CI, 14.9-17.3) in 60-69 year olds. In multivariable logistic regression analyses restricted to subjects aged 40+ years, myopia was associated with younger age (odds ratio [OR], 0.94; 95% Confidence Interval [CI], 0.93-0.94, p < 0.001), education level of university or higher (OR, 2.31; CI, 1.97-2.71, p < 0.001), and shorter sunlight exposure time (OR, 0.84; CI, 0.76-0.93, p = 0.002). CONCLUSIONS This study provides the first representative population-based data on refractive error for Korean adults. The prevalence of myopia in Korean adults in 40+ years (34.7%) was comparable to that in other Asian countries. These results show that the younger generations in Korea are much more myopic than previous generations, and that important factors associated with this increase are increased education levels and reduced sunlight exposures

BanditPAM++: Faster kk-medoids Clustering

Clustering is a fundamental task in data science with wide-ranging applications. In $k$-medoids clustering, cluster centers must be actual datapoints and arbitrary distance metrics may be used; these features allow for greater interpretability of the cluster centers and the clustering of exotic objects in $k$-medoids clustering, respectively. $k$-medoids clustering has recently grown in popularity due to the discovery of more efficient $k$-medoids algorithms. In particular, recent research has proposed BanditPAM, a randomized $k$-medoids algorithm with state-of-the-art complexity and clustering accuracy. In this paper, we present BanditPAM++, which accelerates BanditPAM via two algorithmic improvements, and is $O(k)$ faster than BanditPAM in complexity and substantially faster than BanditPAM in wall-clock runtime. First, we demonstrate that BanditPAM has a special structure that allows the reuse of clustering information $\textit{within}$ each iteration. Second, we demonstrate that BanditPAM has additional structure that permits the reuse of information $\textit{across}$ different iterations. These observations inspire our proposed algorithm, BanditPAM++, which returns the same clustering solutions as BanditPAM but often several times faster. For example, on the CIFAR10 dataset, BanditPAM++ returns the same results as BanditPAM but runs over 10$\times$ faster. Finally, we provide a high-performance C++ implementation of BanditPAM++, callable from Python and R, that may be of interest to practitioners at https://github.com/motiwari/BanditPAM. Auxiliary code to reproduce all of our experiments via a one-line script is available at https://github.com/ThrunGroup/BanditPAM_plusplus_experiments.Comment: NeurIPS 202