760 research outputs found
Basic Incompatibilities Between Evolutionary and Behavioral Archaeology
Schiffer (1996) recently proposed that, despite some incompatibilities, considerable common ground exists between behavioral archaeology and evolutionary or selectionist, archaeology. He concludes that there is no fundamental reason why the two approaches cannot work in concert to explain human behavioral change. There are, however, several important reasons why the two programs, at least as currently conceived, cannot work together in any thoroughly integrated fashion. Although both programs employ inference, behavioral archaeology conflates the distinct roles of configurational and immanent properties, searches for nomothetic answers to questions about human behavior, overlooks historical contingency when inferring and explaining the nature of past behavior, and in some cases seems to fall back on vitalism as the mechanism of change. Evolutionary archaeology employs immanent properties inferentially, explicitly acknowledges the importance of the historical contingencies of configurational properties, explains human behavior as being time- and spacebound, and calls upon selection and drift (transmission) as the mechanisms of change. Any attempt to integrate the two approaches must begin by addressing these basic differences
Latent Lab: Large Language Models for Knowledge Exploration
This paper investigates the potential of AI models, particularly large
language models (LLMs), to support knowledge exploration and augment human
creativity during ideation. We present "Latent Lab" an interactive tool for
discovering connections among MIT Media Lab research projects, emphasizing
"exploration" over search. The work offers insights into collaborative AI
systems by addressing the challenges of organizing, searching, and synthesizing
content. In a user study, the tool's success was evaluated based on its ability
to introduce users to an unfamiliar knowledge base, ultimately setting the
groundwork for the ongoing advancement of human-AI knowledge exploration
systems
1862-08-19 Mark Dunnell forwards request for payment for his officers
https://digitalmaine.com/cw_me_5th_regiment_corr/1454/thumbnail.jp
Using Learning Collaboratives to Improve Public Health Emergency Preparedness Systems
The U.S. National Health Security Strategy calls for the development and wide-spread implementation of quality improvement (QI) tools in public health emergency preparedness (PHEP), including the development of “learning collaboratives,” a structured way for organizations with common interests to close the gap between potential and practice by learning from each other. To test this approach, we developed and assessed separate learning collaboratives focused on PHEP emergency communications and on the use of Medical Reserve Corps (MRC) volunteers. Although participants carried out improvement projects that they felt were useful, each collaborative struggled to identify a common theme, participation was limited, and leadership buy-in was not strong. This suggests that the learning collaborative model may not be appropriate in this context. Because some of the factors that limited their success are inherent (the lack of an established evidence base and agreed upon outcome and performance measures and the difficulty of carrying out rapid Plan-Do-Study-Act (PDSA) cycles and measuring the results), this suggests that the learning collaborative model may not be appropriate in this context
1862-07-24 Mark Dunnell recommends Lieutenant Samuel Munson for commission as Major in a new regiment
https://digitalmaine.com/cw_me_5th_regiment_corr/1427/thumbnail.jp
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