Yuji Yoshimura,
Yuji Yoshimura
Institution:
Email:
Anne Krebs,
Anne Krebs
Institution:
Email:
Carlo Ratti
Carlo Ratti
Institution:
Email:
This paper introduces network science to museum studies. The spatial structure of the museum and the exhibit display largely determine what visitors see and in which order, thereby shaping their visit experience. Despite the importance of spatial properties in museum studies, few scientific tools ha...
More
This paper introduces network science to museum studies. The spatial structure of the museum and the exhibit display largely determine what visitors see and in which order, thereby shaping their visit experience. Despite the importance of spatial properties in museum studies, few scientific tools have been developed to analyze and compare the results across museums. This paper introduces the six habitually used network science indices and assesses their applicability to museum studies. Network science is an empirical research field that focuses on analyzing the relationships between components in an attempt to understand how individual behaviors can be converted into collective behaviors. By taking the museum and the visitors as the network, this methodology could reveal unknown aspects of museum functions and visitor behavior, which could enhance exhibition knowledge and lead to better methods for creating museum narratives along the routes.
Less
Posted 1 week ago
David Rozado
David Rozado
Institution:
Email:
I report here a comprehensive analysis about the political preferences embedded in Large Language Models (LLMs). Namely, I administer 11 political orientation tests, designed to identify the political preferences of the test taker, to 24 state-of-the-art conversational LLMs, both closed and open sou...
More
I report here a comprehensive analysis about the political preferences embedded in Large Language Models (LLMs). Namely, I administer 11 political orientation tests, designed to identify the political preferences of the test taker, to 24 state-of-the-art conversational LLMs, both closed and open source. When probed with questions/statements with political connotations, most conversational LLMs tend to generate responses that are diagnosed by most political test instruments as manifesting preferences for left-of-center viewpoints. This does not appear to be the case for five additional base (i.e. foundation) models upon which LLMs optimized for conversation with humans are built. However, the weak performance of the base models at coherently answering the tests’ questions makes this subset of results inconclusive. Finally, I demonstrate that LLMs can be steered towards specific locations in the political spectrum through Supervised Fine-Tuning (SFT) with only modest amounts of politically aligned data, suggesting SFT’s potential to embed political orientation in LLMs. With LLMs beginning to partially displace traditional information sources like search engines and Wikipedia, the societal implications of political biases embedded in LLMs are substantial.
Less
Posted 1 week ago
Lars K. Hallstrom
Lars K. Hallstrom
Institution:
Email:
Posted 1 week ago
Evan Thomas
Evan Thomas
Institution:
Email:
Posted 1 week ago
Lena Spieth,
Lena Spieth
Institution:
Email:
Mikael Simons
Mikael Simons
Institution:
Email:
Posted 1 week ago
Nicholas J. L. Brown
Nicholas J. L. Brown
Institution:
Email:
During the last decade, there has been a substantial acceleration in the open science movement. Most people would probably hope to have seen signs of positive change in that time, yet it seems that the process of improving the practice of science is moving at a glacial pace.
Posted 1 week ago
Reuven Cohen,
Reuven Cohen
Institution:
Email:
Oren Perez
Oren Perez
Institution:
Email:
In this article we study the social dynamic of temporal partitioning congestion games (TPGs), in which participants must coordinate an optimal time-partitioning for using a limited resource. The challenge in TPGs lies in determining whether users can optimally self-organize their usage patterns. Rea...
More
In this article we study the social dynamic of temporal partitioning congestion games (TPGs), in which participants must coordinate an optimal time-partitioning for using a limited resource. The challenge in TPGs lies in determining whether users can optimally self-organize their usage patterns. Reaching an optimal solution may be undermined, however, by a collectively destructive meta-reasoning pattern, trapping users in a socially vicious oscillatory behavior. TPGs constitute a dilemma for both human and animal communities. We developed a model capturing the dynamics of these games and ran simulations to assess its behavior, based on a 2×2 framework that distinguishes between the players’ knowledge of other players’ choices and whether they use a learning mechanism. We found that the only way in which an oscillatory dynamic can be thwarted is by adding learning, which leads to weak convergence in the no-information condition and to strong convergence in the with-information condition. We corroborated the validity of our model using real data from a study of bats’ behaviour in an environment of water scarcity. We conclude by examining the merits of a complexity-based, agent-based modelling approach over a game-theoretic one, contending that it offers superior insights into the temporal dynamics of TPGs. We also briefly discuss the policy implications of our findings.
Less
Posted 1 week ago
Ayenew Guadu
Ayenew Guadu
Institution:
Email:
The general objective of this intertextual analysis’s was to explore Wolde’s novel Defend the Name (1969) with the view to identify and interpret the several thematic and stylistic intertexts that are woven throughout the narrative. Based on available research, there is a scarcity of critical st...
More
The general objective of this intertextual analysis’s was to explore Wolde’s novel Defend the Name (1969) with the view to identify and interpret the several thematic and stylistic intertexts that are woven throughout the narrative. Based on available research, there is a scarcity of critical studies that have utilized the theory of intertextuality for the analysis and interpretation of Ethiopian prose fiction in English, particularly within the novel genre. The current study was aimed to partially fill in this critical gap. In doing so, the theory of intertextuality is employed as theoretical-analytical framework of the study. The findings of this intertextual analysis concentrated on the thematic and stylistic intertexts that were woven throughout the plot of the book Defend the Name. These intertexts included biblical allusions, colonial literary devices, contemporary theoretical and ideological works, and cultural and historical discourses that the book intertextually engages with in addition to other literary and nonliterary works. This study provides insightful information about the thematic diversity of Defend the Name and its involvement with multiple intertexts through its intertextual analysis. It enhances the reader’s comprehension of the story, characters, and larger sociopolitical situations that the novel addresses, demonstrating the author’s skill in fusing together a variety of literary, scriptural, ideological, and cultural aspects.
Less
Posted 1 week ago
Ofer N. Gofrit,
Ofer N. Gofrit
Institution:
Email:
Ariel Aviv
Ariel Aviv
Institution:
Email:
Cancer is a consequence of stochastic (mutations, genetic, and epigenetic instabilities) and deterministic (evolutionary bottlenecks) events. Stochastic events are less amenable to prediction, whereas deterministic events yield more predictable results. The relative contribution of these opposing fo...
More
Cancer is a consequence of stochastic (mutations, genetic, and epigenetic instabilities) and deterministic (evolutionary bottlenecks) events. Stochastic events are less amenable to prediction, whereas deterministic events yield more predictable results. The relative contribution of these opposing forces determines cancer predictability, which affects the accuracy of our prognostic predictions and is critical for treatment planning. In this study, we attempted to quantify predictability. The predictability index (PI) was defined as the median overall-survival at any time point divided by the standard error at that time. Using data obtained from the SEER program, we found striking differences in the PI of different tumors. Highly predictable tumors were malignancies of the breast, thyroid, prostate, and testis (5-year PI of 3516, 1920, 1919, and 1805, respectively). Less predictable tumors were colorectal, melanoma, and bladder (5-year PI of 1264, 1197, and 760, respectively). Least predictable were pancreatic cancer and chronic myelogenous leukemia (5-year PI of 129, and 42). PI decreased during follow-up in all examined tumors and showed sex differences in some cases. Thyroid cancer was significantly more predictable in women (5-year PI of 2579 vs. 748, p = 0.00017) and bladder cancer more predictable in men (5-year PI of 723 vs. 385, p = 0.012), Predictability is a potentially new distinguishing feature of malignancy. This study sheds light on prognostic accuracy and provides insight into the relative roles of stochastic and deterministic forces during carcinogenesis.
Less
Posted 1 week ago
Youngsam Chun,
Youngsam Chun
Institution:
Email:
Jisoo Hur,
Jisoo Hur
Institution:
Email:
Junseok Hwang
Junseok Hwang
Institution:
Email:
This study investigates the factors influencing specialization in artificial intelligence (AI) technology, a critical element of national competitiveness. We utilized a revealed comparative advantage matrix to evaluate technological specialization across countries and employed a three-way fixed-effe...
More
This study investigates the factors influencing specialization in artificial intelligence (AI) technology, a critical element of national competitiveness. We utilized a revealed comparative advantage matrix to evaluate technological specialization across countries and employed a three-way fixed-effect panel logit model to examine the relationship between AI specialization and its determinants. The results indicate that the development of AI technology is strongly contingent on a nation’s pre-existing technological capabilities, which significantly affect AI specialization in emerging domains. Additionally, this study reveals that scientific knowledge has a positive impact on technological specialization, highlighting the necessity of integrating scientific advancements with technological sectors. Although complex technologies positively influence AI specialization, their effect is less pronounced than that of scientific knowledge. This suggests that in rapidly advancing fields, such as AI, incorporating new scientific knowledge into related industries may be more advantageous than simply advancing existing technologies to outpace competitors. This insight points nations toward enhancing AI competitiveness in new areas, emphasizing the vital importance of both scientific and technological capabilities, and the integration of novel AI knowledge with established sectors. This research offers critical guidance for policymakers in less technologically and economically developed countries, as these nations may not have the technological infrastructure required to foster AI specialization through increased technical complexity.
Less
Posted 1 week ago