Learning to be Human Together

This project is made possible with funding by the Government of Ontario and through eCampusOntario’s support of the Virtual Learning Strategy.I. Come On InII. The Modules (1-4)III. OutroIV. Some Things We Picked Up & Take EverythingThis resource explores what humanizing teaching and learning means: to acknowledge that our relationships are foundational to the work that we do. It means to make learning inclusive with connection, access, and meaning-making at its core. When you have something to say that you hope can empower people and encourage inclusion you yell it from the rooftops and in as many formats as possible. To that end, you will find the materials of this project in a number of formats — to meet you where you are and how YOU choose to interact with it. This is just the beginning of what we hope will be a deeply humanized experience. This material is not a book, nor a guide, nor a checklist–it’s an engagement with complex issues, with social entanglements, and with ways of doing (and not doing) things. This work also foregrounds the importance of twelve core super themes, such as trust, vulnerability, re-framing failure, and friction. These super themes are not discrete units or siloed entities, rather they are multi-layered ideas that intersect and weave together across the humanizing learning spectrum. Module 1: Unlearning & Unsettling. How do we know what we know and what is our educational value system? To move forward, we must interrogate our teaching and learning practices - the work of unlearning and unsettling. This module explores how the process is more important than the outcome, and highlights the importance of moving slowly, giving ourselves time to think, process, and reflect. Module 2: Students as Agents of the own Diverse Destiny. This module explores the importance and role of vulnerability and failure in humanizing learning. It emphasizes that we are all learning and explores how, since education is relational, power is especially present. Module 3: Co-Creating Inclusive Communities. This module acknowledges that diversity is our greatest asset, with inclusion being our most important challenge. It explores community guidelines, participation standards, ethics, social justice, co-design and co-creation, and highlights how these concepts can fundamentally challenge and disrupt power. Module 4: Sustaining Change. This module acknowledges that change is hard. How can we sustain change, complexity, and care in a system that was not designed for what our society demands of it? How do we foreground care and frame it as a reciprocal process? This module explores this apparent friction and highlights steps we can take to make this work both foundational and sustainable. This resource also includes an exploration of the co-design experience - the process of creating and nurturing a community that collectively did this work. Coming out the other side of this work are a group of people who came together to share our love for learning and our passion for education. We hope you find something here that changes even one small aspect of how you move through the world

Grand challenges in social physics: in pursuit of moral behavior

Methods of statistical physics have proven valuable for studying the evolution of cooperation in social dilemma games. However, recent empirical research shows that cooperative behavior in social dilemmas is only one kind of a more general class of behavior, namely moral behavior, which includes reciprocity, respecting others' property, honesty, equity, efficiency, as well as many others. Inspired by these experimental works, we here open up the path toward studying other forms of moral behavior with methods of statistical physics. We argue that this is a far-reaching direction for future research that can help us answer fundamental questions about human sociality. Why did our societies evolve as they did? What moral principles are more likely to emerge? What happens when different moral principles clash? Can we predict the break out of moral conflicts in advance and contribute to their solution? These are amongst the most important questions of our time, and methods of statistical physics could lead to new insights and contribute toward finding answers

What makes icons appealing? The role of processing fluency in predicting icon appeal in different task contexts.

Although icons appear on almost all interfaces, there is a paucity of research examining the determinants of icon appeal. The experiments reported here examined the icon characteristics determining appeal and the extent to which processing fluency - the subjective ease with which individuals process information - was used as a heuristic to guide appeal evaluations. Participants searched for, and identified, icons in displays. The initial appeal of icons was held constant while ease of processing was manipulated by systematically varying the complexity and familiarity of the icons presented and the type of task participants were asked to carry out. Processing fluency reliably influenced users' appeal ratings and appeared to be based on users' unconscious awareness of the ease with which they carried out experimental tasks

Governmental Institutions as Agents of Change: Rethinking American Political Development in the Early Republic, 1787-1835

During the past few years, a new generation of historians have turned their attention to the influence of law, public policy, and public administration in American life in the period between 1787 and 1835. The purpose of this essay is to highlight the contributions of these scholars in the hope that such an inquiry can further the ongoing interdisciplinary dialogue on American political development between historians, political scientists, and historical sociologists

From Isotropic to Anisotropic Side Chain Representations: Comparison of Three Models for Residue Contact Estimation

The criterion to determine residue contact is a fundamental problem in deriving knowledge-based mean-force potential energy calculations for protein structures. A frequently used criterion is to require the side chain center-to-center distance or the -to- atom distance to be within a pre-determined cutoff distance. However, the spatially anisotropic nature of the side chain determines that it is challenging to identify the contact pairs. This study compares three side chain contact models: the Atom Distance criteria (ADC) model, the Isotropic Sphere Side chain (ISS) model and the Anisotropic Ellipsoid Side chain (AES) model using 424 high resolution protein structures in the Protein Data Bank. The results indicate that the ADC model is the most accurate and ISS is the worst. The AES model eliminates about 95% of the incorrectly counted contact-pairs in the ISS model. Algorithm analysis shows that AES model is the most computational intensive while ADC model has moderate computational cost. We derived a dataset of the mis-estimated contact pairs by AES model. The most misjudged pairs are Arg-Glu, Arg-Asp and Arg-Tyr. Such a dataset can be useful for developing the improved AES model by incorporating the pair-specific information for the cutoff distance

Experimental evidence on trading behavior, market efficiency and price formation in double auctions with unknown trading duration

The reasons for the highly efficient market outcomes observed under the double auction remain unclear. This paper presents a series of experimental financial markets designed to investigate the importance of unknown trading period duration on trading behavior and the convergence tendencies of such markets. Using panel data techniques the results support the conclusions that individuals generally display more aggressive trading strategies, trading earlier in a period, and that markets exhibit reduced levels of informational efficiency when unknown duration is present. Markets with imperfect information structures are also studied and, in a unique result, are associated with significantly slower rates of trade, as traders become more cautious over their trading strategies. Investigation of the price formation process provides evidence that the pricing error varies over time and the estimation of a fixed effects model provides unique support that learning effects and unknown trading period duration influence the price formation process. Future refinement of theoretical models of the price formation process or institutions of exchange should recognize the effect of unknown trading period duration on market behavior, along with potential learning effects. Copyright © 2005 John Wiley & Sons, Ltd.

Estimation of a Tobit model with unknown censoring threshold

Conventional wisdom suggests that only the estimated intercept is affected by imposition of a zero censoring threshold on a Tobit model. This is true for Heckman-Lee estimation. For maximum likelihood (ML) estimation, however, it is only true if the censoring threshold is known and is subtracted from the dependent variable. Failure to properly transform the dependent variable prior to ML estimation of a zero threshold Tobit model will generally bias the coefficient estimates. A long neglected topic is ML estimation of a Tobit model with common, but unknown, censoring threshold. This paper shows that the ML estimator of the censoring threshold is the minimum order statistic from the observed subsample, and that existing software for estimation of a zero-threshold Tobit model is easily adapted to include estimation of the censoring threshold.